Complete genome assembly and functional characterization of Brucella melitensis strain IMHB1 from a clinical isolate in Inner Mongolia, China

Brucellosis is a globally prevalent zoonotic disease caused by Brucella species, posing a significant threat to both public health and the livestock industry. Despite ongoing research efforts, the mechanisms underlying Brucella pathogenesis remain poorly understood, particularly for strains isolated from specific geographical regions. A Brucella melitensis biotype III strain, IMHB1, was isolated from the blood culture of a patient in Hulunbuir, Inner Mongolia, China, who had experienced multiple relapses of brucellosis. Using Oxford Nanopore long-read sequencing, a complete 3.32 Mbp genome was assembled comprising two circular chromosomes with a GC content of 57.22% and 3,152 predicted coding sequences. Phylogenetic analysis revealed that IMHB1 was closely related to the cgST-588 type. Comprehensive genomic characterization identified mobile genetic elements, horizontally transferred regions, and prophage insertions. Functional annotation detected 10 genomic islands, 45 carbohydrate-active enzymes, 3 biosynthetic gene clusters, 4 antibiotic resistance genes, 20 eggNOG categories, and 252 KEGG pathways. Moreover, 66 predicted virulence factors and 18 experimentally verified proteins associated with pathogen-host interactions were identified, suggesting their potential roles in virulence and host adaptation. Based on extensive bioinformatics analysis, this study provides novel insights into the genomic characteristics and potential pathogenic mechanisms of Brucella melitensis strain IMHB1, enriching existing genomic resources and contributing to future research on brucellosis pathogenesis and therapeutic strategies.

1 Introduction

Brucellosis is a globally contagious zoonosis caused by Brucella spp., imposing significant human and economic burdens. Over 500,000 new human cases are reported annually worldwide (Corbel, 2016), and a meta-analysis of surveillance data estimated the annual number of cases could reach up to 2.1 million, highlighting ongoing underreporting (Laine et al., 2023). Recent data indicate that the prevalence of brucellosis has expanded from 53 to at least 97 countries, with Kenya exhibiting the highest incidence, reaching 293.1 cases per 100,000 in 2019 (Liu et al., 2024). The disease causes significant losses to agriculture, animal husbandry, public health, and the social economy. Brucella, a facultative intracellular gram-negative coccobacillus, is the causative agent of brucellosis. Twelve Brucella spp. have been described, including Brucella melitensis, B. abortus, B. suis, B. ovis, B. canis, B. neotomae, B. ceti, B. pinnipedialis, B. microti, B. inopinata, and B. papionis (Whatmore et al., 2014; Scholz et al., 2016). Among these, B. melitensis is the most common human-infecting species and exhibits high virulence (Głowacka et al., 2018). Unlike many pathogens, Brucella lacks exotoxins and plasmid-encoded toxins but employs stealth strategies to persist intracellularly (Barquero-Calvo et al., 2007; Conde-Álvarez et al., 2012). Its key virulence characteristics include prolonged survival within host cells and evasion of the host immune system, ultimately leading to chronic infection.

Brucella is primarily transmitted to humans through the consumption of unpasteurized dairy products or direct contact with infected animals (Corbel, 2016). It is highly infectious, with an aerosol dose as low as 10–100 organisms (Bossi et al., 2004). Upon infection with Brucella, humans exhibit nonspecific symptoms such as fever, headache, arthralgia, myalgia, fatigue, and sweating. Despite extensive research, the mechanisms by which Brucella induces pathological changes across organs remain poorly understood. Additionally, genomic data for Brucella isolates from Inner Mongolia are limited, hindering region-specific control strategies. A comprehensive understanding of Brucella’s biological characteristics is therefore essential to elucidate its pathogenic processes and mechanisms.

Advances in sequencing technologies, such as Illumina and Oxford Nanopore, coupled with the development of refined and widely adopted databases, have greatly accelerated genomic studies of bacterial pathogens. For instance, the virulence factor database (VFDB) is used for virulence factor identification, the comprehensive antibiotic resistance database (CARD) for antibiotic resistance gene screening, and Proksee for genome assembly and visualization (Liu et al., 2022; Alcock et al., 2023; Grant et al., 2023). However, at the time of writing, only 387 Brucella genomes at the chromosomal and complete assembly levels were available in the national center for biotechnology information (NCBI) Genome database, compared with 7,660 for Escherichia coli and 2,904 for Staphylococcus aureus, indicating that research on Brucella has received limited attention.

The first B. melitensis 16M genome, published in 2002, provided foundational insights into the structural and functional characteristics of this species (DelVecchio et al., 2002). Advances in long-read sequencing technologies now enable high-quality de novo assembly of Brucella genomes, revealing >97% sequence similarity among strains (DelVecchio et al., 2002). Nevertheless, individual strains exhibit distinct virulence, host preferences, and zoonotic potential (Suárez-Esquivel et al., 2017; Sheppard et al., 2018), and their clustering patterns correspond to the geographical region of the preferred host (Moreno, 2014; Vergnaud et al., 2018; Suárez-Esquivel et al., 2020).

We present the complete genome sequence of the clinical isolate IMHB1 from Inner Mongolia and perform comparative analyses to identify its genomic features and virulence determinants. B. melitensis strain IMHB1 was isolated from the blood of a patient with brucellosis in Hulunbuir, Inner Mongolia, China, and identified by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS), AMOS PCR assay, and monospecific agglutination tests. The genome was sequenced and de novo assembled, followed by core-genome multilocus sequence typing (cgMLST) genotyping, structural characterization, and functional annotation. Biological pathways and pathogenic molecules were analyzed and predicted, providing a foundation for investigating the pathogenic mechanisms of Brucella.

2 Materials and methods

2.1 Clinical information

A 55-year-old male patient presented with low-grade fever, excessive sweating, and fatigue for >20 days and had experienced multiple episodes of brucellosis over the past 5 years. The patient was diagnosed with Brucella infection using the Rose Bengal plate agglutination test (RBPT), serum agglutination test (SAT), and blood culture according to the Diagnostic Criteria for Brucellosis issued by the Health Department of the People’s Republic of China (National Health Commission of the People’s Republic of China, 2019). The RBPT result was positive, and the SAT titer was 1:400++. The blood culture flagged positive at 2.98 days, and based on the growth curve characteristics, Brucella growth was strongly suspected. The patient received intravenous doxycycline and levofloxacin for 14 days, resulting in significant clinical improvement and a negative blood culture, and the patient was followed by oral administration of both drugs for an additional 6 weeks.

2.2 Ethics statement

The patient was informed about the purpose and procedures of this study and provided written informed consent. All experimental procedures were approved by the Ethics Committee of Hulunbuir People’s Hospital.

2.3 Genomic and microbiological techniques

Strain IMHB1, isolated from the patient’s blood, was identified at the genus, species, and biotype levels by MALDI-TOF MS, AMOS PCR, and monospecific agglutination tests, respectively. As illustrated in Figure 1, the DNA of strain IMHB1 was sequenced on PromethION sequencer and Illumina NovaSeq platforms, and a complete genome map was constructed. Genome features and functions were analyzed using Proksee (Grant et al., 2023), R software (R Core Team, 2022), and specialized functional tools and databases, including public databases for molecular typing and microbial genome diversity (PubMLST) (Jolley et al., 2018), phage search tool with enhanced sequence translation (PHASTEST) (Wishart et al., 2023), an integrated interface for computational identification and visualization of genomic islands (IslandViewer 4) (Bertelli et al., 2017), carbohydrate-active enzymes (CAZy) database (Lombard et al., 2024), CARD (Alcock et al., 2023), antibiotics and secondary metabolite analysis shell (antiSMASH) (Blin et al., 2023), evolutionary genealogy of genes: non-supervised orthologous groups (eggNOG) database (Huerta-Cepas et al., 2018), kyoto encyclopedia of genes and genomes (KEGG) database (Kanehisa and Goto, 2000), VFDB (Liu et al., 2022), and pathogen host interactions (PHI-base) database (Urban et al., 2022).

Figure 1

Figure 1. Experimental procedures. Strain IMHB1, isolated from the blood of a patient with brucellosis, was identified at the genus, species, and biotype levels by MALDI-TOF MS, AMOS PCR, and monospecific agglutination test, respectively. Genomic DNA of strain IMHB1 was then sequenced using the PromethION and Illumina NovaSeq platforms, followed by genome assembly and completion mapping. The genomic features and functional annotations of strain IMHB1 were analyzed using PubMLST, Proksee, R software, PHASTEST, IslandViever 4, CAZy, CARD, antiSMASH, eggNOG, KEGG, VFDB, and PHI-base databases.

2.4 Bacterial isolation and identification

Strain IMHB1 was obtained from the blood of a patient with brucellosis at Hulunbuir People’s Hospital (Hulunbuir, Inner Mongolia, China). Blood (10 mL) was collected in a disposable culture bottle containing 30 mL of compounded medium with polymeric adsorbent beads (bioMérieux, Lyon, Rhone, France). The medium comprised of peptone, anticoagulants, vitamins, amino acids, carbon sources, and trace elements, and the bottles were filled with N₂, O₂, and CO₂. The blood-containing bottles were incubated in a BACT/ALTERT 3D 240 automated culture instrument (bioMérieux, Lyon, Rhone, France) and monitored for microbial growth over 7 days by performing optical inspection every 10 minutes.

Growth was detected after 2.98 day by an automated culture instrument, after which the culture was transferred to Columbia blood agar plates (Autobio, Zhengzhou, Henan, China) and incubated at 37°C with 5% CO₂ for 5 days. Protein extraction was performed to identify the bacterial genus. followed by MALDI-TOF MS (Zybio, Chongqing, China). DNA was extracted using a QIAGEN kit (Hilden, Germany) for species identification via AMOS PCR. Colonies were harvested for biotype determination using monospecific serum A and M agglutination tests (Tsingtao Sinova HK Biotechnology, Qingdao, Shandong, China).

2.5 AMOS PCR amplification

The extracted DNA was subjected to multiplex AMOS PCR (TransGen, Beijing, China). Primer sequences are listed in Table 1, and all primers were synthesized by Sangon Biotech Co., Ltd. (Shanghai, China). Primer P_IS711 was used at a final concentration of 1 µM, and other primers at 0.2 µM. The PCR program was 95°C for 5 min, 30 cycles at 95°C for 1 min, 60°C for 1 min, and 72°C for 1 min, followed by 72°C for 10 min.

Table 1

Table 1. Oligonucleotide primers used in the AMOS-PCR assay.

2.6 Sequencing and genome assembly

The extracted DNA was quantified using a Qubit 3.0 fluorometer (ThermoFisher Scientific, Waltham, Massachusetts, U.S.A.) at 67 ng/μL. Purity was assessed by NanoDrop spectrophotometry (ThermoFisher Scientific, Waltham, Massachusetts, U.S.A.), with OD260/280 and OD260/230 ratios of 1.94 and 1.89, respectively. Fragment size analysis indicated that the predominant DNA fragments were greater than 20 kb.

DNA was purified by magnetic bead separation, damage-repaired, end-repaired, and ligated to barcode tags and sequencing adapters. The processed DNA was loaded onto an R9.4 sequenced chip for genomic sequencing on a PromethION sequencer using Oxford Nanopore long-read sequencing (Oxford Nanopore Technologies, Oxford, UK) and yielded an average depth of 591× relative to this genome. Simultaneously, short-read data were generated to create a high-quality draft assembly on an Illumina NovaSeq platform using Illumina short-read sequencing (Illumina, San Diego, California, U.S.A.), yielding an average depth of 448× coverage. Sequencing was performed by OE Biotech Co. Ltd. (Shanghai, China). Unicycler v0.4.9 was used for genome assembly, and Pilon v1.23 was employed to correct errors and generate high-accuracy assembled genomic data. Assembly quality was assessed with QUAST v5.0, achieving an N50 of 2,126,219 bp.

2.7 Genomic data collection

Fourteen Brucella genomes were retrieved from the NCBI Genome database on October 12, 2025, including two reference strains (B. melitensis 16M and B. abortus 554) and 12 strains isolated in China. The genomes of the isolated strains were selected based on the following criteria: B. melitensis, complete assemblies, with clearly documented host and geographical origin. Detailed information on each genome, including the GenBank assembly ID, species, host, and geographical location, is provided in Supplementary Table S1.

2.8 cgMLST and Phylogenetic reconstruction

cgMLST was performed for all 15 Brucella genomes using the schemes available on the PubMLST database (https://pubmlst.org/brucella/). The obtained allelic profiles were used to construct a pairwise Manhattan distance matrix representing the number of allelic mismatches between strains. A phylogenetic tree was subsequently constructed from this distance matrix using the Neighbor-Joining (NJ) algorithm in R v4.5.1 with the ape package v5.8-1. The robustness of the phylogenetic inference was evaluated with 1,000 bootstrap replicates. The final tree was visualized and annotated using the ggtree package v3.16.3.

2.9 Bioinformatics analysis

The integrated Bakta (Schwengers et al., 2021) v1.9 (httpsgithubcomoschwengersbakta), a command-line application for bacterial genome annotation, was applied to analyze the genomic structural characteristics using default parameters. Built-in tools within Bakta include Prodigal for predicting coding sequences (CDSs), tRNAscan-SE for transfer RNAs (tRNAs), Aragorn for transfer-messenger RNAs (tmRNAs), Infernal for ribosomal RNAs (rRNAs) and non-coding RNAs (ncRNAs), CRISPRCasFinder for clustered regularly interspaced short palindromic repeats (CRISPR), and NCBI BLAST+ v2.16 for identifying the origin of replication. Repeat elements were predicted using RepeatModeler v2.0.5 and RepeatMasker v4.1.5. The genomic circular map was visualized online using the Proksee system (https://proksee.ca/).

Potential horizontal gene transfer events were predicted using Alien Hunter (Vernikos and Parkhill, 2006) v1.7 with default parameters. Mobile genetic elements were annotated using MobileOG-db v1.1. Phage genomic sequences were predicted online using the PHASTEST database in deep mode (https://phastest.ca/). Genomic islands (GIs) were identified using IslandViewer 4 (https://www.pathogenomics.sfu.ca/islandviewer/) with default bacterial genome settings.

Carbohydrate-active enzymes (CAZymes) were predicted using HMMER against the database for carbohydrate-active enzyme notation (dbCAN) (https://bcb.unl.edu/dbCAN2/) and DIAMOND against the CAZy database (https://www.cazy.org/). Antimicrobial resistance genes were identified using RGI v6.0 against the CARD (https://card.mcmaster.ca/) under strict criteria. Biosynthetic gene clusters (BGCs) were predicted using antiSMASH v7.0 with default bacterial settings.

The complete assembly of B. melitensis strain IMHB1 was functionally annotated using eggNOG-mapper v2.0 against the eggNOG database (https://eggnogdb.org/) with default parameters. Annotation was performed in HMMER mode to assign COG and KEGG pathway functional categories, and results were visualized using the ggplot2 package v3.5.1 in R v4.5.1. Virulence factors were annotated using NCBI BLAST+ v2.16 against the VFDB core database (http://www.mgc.ac.cn/VFs/) with default parameters. Interactions between the pathogen and host were analyzed using NCBI BLAST+ v2.16 against the PHI database (http://www.phi-base.org/) with default parameters.

3 Results

3.1 Isolation and identification of strain IMHB1

A blood sample (internal ID: 125013166875) collected on January 31, 2025, was cultured in an automated culture instrument which detected a positive signal for microbial growth after 2.98 days. The culture was then transferred to a Columbia blood agar plate and incubated at 37°C and 5% CO₂ for 5 days. The isolate was identified as a member of the Brucella genus by MALDI-TOF MS, with a log(score) ≥2.0 indicating genus-level identification. Based on the AMOS PCR amplicon size shown in Table 1, the amplified fragment (750 bp) corresponded to that of B. melitensis strain M5, suggesting that strain IMHB1 belongs to B. melitensis (Figure 2A). The relative integrated density of the 750 bp band in each lane was quantified using ImageJ2 to confirm specificity (Figure 2B). Agglutination tests with B. monospecific sera A and M were positive, confirming that the B. melitensis isolate belongs to biotype III. This strain was designated IMHB1, indicating its origin from Hulunbuir, Inner Mongolia.

Figure 2

Figure 2. Identification of strain IMHB1 by AMOS PCR. (A) Amplified fragment of strain IMHB1 obtained by AMOS PCR. Lane M: Trans2K DNA marker; Lane 1: Brucella suis strain S2; Lane 2: Brucella strain IMHB1; Lane 3: Brucella melitensis strain M5. (B) Relative integrated density (IntDen) of the 750 bp band (left) in each lane. The integrated density of the DNA band was quantified three times using ImageJ2, and data were expressed as the mean ± standard deviation (SD).

3.2 cgMLST genotyping

The comparative cgMLST analysis of 15 Brucella genomes from the PubMLST database, including strain IMHB1, revealed 15 distinct cgMLST sequence types (cgSTs), demonstrating substantial genetic diversity among the isolates. Strain IMHB1 showed no exact match in the database; its closest related profile was cgST-588, differing at five loci. The phylogenetic tree based on cgMLST allelic profiles grouped the 15 strains into nine primary clusters (Figure 3). Within this phylogeny, IMHB1 exhibited a close evolutionary relationship with two other human-derived B. melitensis strains from Inner Mongolia, whereas a sheep-derived strain from the same region was most closely related to the reference strain B. melitensis 16M.

Figure 3

Figure 3. CgMLST genotyping and phylogenetic analysis. CgMLST analysis resolved the 15 strains into 15 distinct cgSTs. A phylogenetic tree constructed based on the cgMLST allelic profiles grouped these strains into nine primary clusters. Green represents strains isolated from humans, whereas pink represents strains isolated from animals. Phylogenetic inference robustness was evaluated using 1,000 bootstrap replicates, with bootstrap values shown at each branch point.

3.3 Genomic structural characteristics of strain IMHB1

Genomic DNA from B. melitensis strain IMHB1 was sequenced using Oxford Nanopore long-read and Illumina short-read technologies. De novo assembly achieved 591× Nanopore and 448× Illumina coverage, with an N50 of 2.13 Mbp (Nanopore) and a Q30 of 98.31% (Illumina). BUSCO v5.3.2 analysis against the Rhizobiales odb10 dataset indicated 99.8% completeness. Sequencing and assembly statistics are summarized in Supplementary Table S2, demonstrating high accuracy of base recognition and genome assembly.

As shown in Tables 2 and 3, the genome of B. melitensis strain IMHB1 consisted of two circular chromosomes measuring 2.13 Mbp and 1.19 Mbp, respectively. Chromosome I contained 2038 CDSs, 41 tRNAs, 1 tmRNA, 6 rRNAs, 27 ncRNAs, 80 repeat elements, and 2 oriCs, with a total coding length of 1.82 Mbp. Chromosome II comprised 1114 CDSs, 14 tRNAs, 3 rRNAs, 12 ncRNAs, 38 repeat elements, and 1 oriC (all open reading frames [ORFs] are shown in the genomic circle maps, Figure 4). Coding sequences accounted for 86% of chromosome I and 88% of chromosome II, with 959 and 940 genes per Mbp, respectively. These data reveal strong structural and functional consistency between strain IMHB1 and B. melitensis 16M.

Table 2

Table 2. Statistical data of the genome and predicted genes of Brucella melitensis strains IMHB1 and 16M.

Table 3

Table 3. Statistical data of the genome characteristics of Brucella melitensis strains IMHB1 and 16M.

Figure 4

Figure 4. Completed genomic circle map of Brucella melitensis strain IMHB1. Left: Complete genomic circle map of chromosome I, comprising 2,038 CDSs, 41 tRNAs, one tmRNA, six rRNAs, 27 ncRNAs, and two oriCs. Right: Complete genomic circle map of chromosome II, comprising 1114 CDSs, 14 tRNAs, three rRNAs, 12 ncRNAs, and one oriC. The light purple block represents CDS; red, tRNA; bright blue, ncRNA; green, tmRNA; rose pink, rRNA; black, oriC; the orange-yellow curve, GC content; the light blue curve, GC skew (+); and dark red curve, GC skew (-).

3.4 Genomic functional features of strain IMHB1

The functional genomic features of strain IMHB1 encompassed mobile genetic elements (MGEs), putative horizontal gene transfer (HGT) regions, and prophage regions. The mobile orthologous groups database (MobileOG-db) is an interactive database that catalogs a wide range of proteins regulating the lifecycle of MGEs in bacteria. Five essential functional categories of MGEs were defined: (i) integration and excision (IE) from one genetic locus to another; (ii) replication, recombination, or nucleic acid repair (RRR); (iii) interorganism transfer (T); (iv) element stability, transfer, or defense (STD); and (v) phage-specific (P) biological processes. The MGEs analysis was performed using thresholds of >60% identity, an E-value of <1e-5, and evidence from manual, homology, and keyword searches. A total of 121 MGEs were identified in the genome of B. melitensis strain IMHB1 (Figure 5A), comprising 36 IEs, 29 RRRs, 24 transfers, 6 STDs, and 26 Ps (all MGE regions are shown in Figure 5B).

Figure 5

Figure 5. Genomic functional features of Brucella melitensis strain IMHB1. (A) Composition of 121 mobile genetic elements (MGEs). (B) Distribution of 121 MGEs and 36 putative horizontal gene transfer (HGT) regions across the two chromosomes of strain IMHB1. (C) Location and composition of the integrated phage genome on chromosome I of strain IMHB1.

HGT events were detected using Alien Hunter in Proksee, revealing their distribution across both chromosomes. 17 putative HGT regions, with a combined size of 228,246 bp, were identified on chromosome I, and 19 regions spanning 199,613 bp were detected on chromosome II (Figure 5B; Supplementary Table S3). A prophage region spanning 2,006,080–2,022,067 bp was predicted by PHASTEST with a score of 150, indicating an intact prophage region (score > 90). This region contained 21 ORFs, of which 15 encoded four head proteins, six tail proteins, one regulatory protein, two phage-like proteins, one portal protein, and one terminase (Figure 5C).

3.5 Biological functional annotation of strain IMHB1

Functional annotation of strain IMHB1 identified features related to gene islands, carbohydrate-active enzymes, biosynthetic gene clusters, and antibiotic resistance genes. Seven GIs were predicted to be located on chromosome I (comprising 113 genes) and three on chromosome II (containing 63 genes) by the IslandPath-DAMOB method (Figure 6A). To identify potential virulence islands, genes inside and outside the predicted GIs were annotated against the VFDB database, indicating that no significant enrichment of virulence determinants was observed outside the predicted GIs (P > 0.05).

Figure 6

Figure 6. Biological functional characteristics of Brucella melitensis strain IMHB1. (A) Distribution of predicted gene islands across the two chromosomes of strain IMHB1. Pink represents gene islands predicted by the IslandPath-DIMOB method, and blue represents those predicted by the SIGI-HMM method. (B) Composition of 45 CAZymes predicted using the CAZy database.

A total of 68 and 123 CAZymes were predicted by HMMER and DIAMOND, respectively. The intersection of these two sets revealed 45 overlapping CAZymes, including 18 glycoside hydrolases, 22 glycosyl transferases, 2 auxiliary activities, 2 carbohydrate esterases, and 1 carbohydrate-binding module (Figure 6B; Supplementary Table S4). Compared with B. melitensis 16M, IMHB1 revealed a minor reduction in one glycoside hydrolase family. Three BGCs were detected on chromosome I, including arylpolyene (111,706–152,887 bp), terpene (160,013–180,846 bp), and β-lactone (1,416,579–1,444,388 bp), all of which shared 99% similarity with B. melitensis 16M.

The genome of the IMHB1 strain was screened for antibiotic resistance genes, revealing a high-confidence match to mprF with 99.66% identity, while three additional putative resistance genes (qacG, adeF, and fosXCC) were detected, each exhibiting <60% similarity to known resistance determinants (Table 4). An additional panel of 14 Brucella genomes identified by cgMLST genotyping was screened, showing that the prevalence of the mprF resistance gene was 100%.

Table 4

Table 4. Predicted antibiotic resistance genes in Brucella melitensis IMHB1.

Functional annotation using eggNOG and KEGG indicated broad metabolic capabilities. Annotation of the eggNOG identified 20 COGs; however, most annotated proteins (556) lacked functional characterization. The most abundant functional categories included amino acid transport and metabolism, transcription, inorganic ion transport and metabolism, energy production and conversion, translation, ribosomal structure, and biogenesis (Figure 7A). Furthermore, annotation by the KEGG database revealed 11 metabolism classes, 11 human disease classes, 9 organismal system classes, 5 genetic information processing classes, 4 cellular process classes, and 2 environmental information processing classes (Figure 7B). The top 20 of the 252 KEGG pathways included ABC transporters, two-component systems, purine metabolism, oxidative phosphorylation, and quorum sensing (Figure 7C). Compared to B. melitensis 16M, strain IMHB1 contained CbiM, ArgT, and HisJ in the ABC transporter pathway; PcaF in benzoate degradation; and LepB in the legionellosis pathway, while lacking BioM in the ABC transporter pathway, AdeB in the beta-lactam resistance pathway, and YxdM in the two-component system pathway.

Figure 7

Figure 7. Biological functional annotations of Brucella melitensis strain IMHB1. (A) EggNOG database annotation of genes on the two chromosomes of strain IMHB1. The main functional categories included amino acid transport and metabolism; transcription; inorganic ion transport and metabolism; energy production and conversion; and translation, ribosomal structure, and biogenesis. (B) KEGG database annotation of genes on the two chromosomes at level two. The genes were classified into 11 metabolism classes, 11 human disease classes, nine organismal system classes, five genetic information processing classes, four cellular process classes, and two environmental information processing classes. (C) KEGG database annotation of genes on the two chromosomes at level three. The major pathways included ABC transporters, two-component systems, purine metabolism, oxidative phosphorylation, and quorum sensing.

3.6 Prediction of pathogenic molecules of strain IMHB1

Virulence factors of strain IMHB1 were predicted using BLASTP against the VFDB core dataset under a threshold of >80% identity, alignment length of >100 amino acids, and E-value < 1e-10. A total of 66 virulence factors were identified, including 6 factors related to adherence, 25 to effector delivery systems, 33 to immune modulation, and 2 to regulation, respectively (Table 5). Compared with B. melitensis 16M, strain IMHB1 lacked BtaF (VF1343) in the adherence category.

Table 5

Table 5. Categories and functional characteristics of predicted virulence factors in Brucella melitensis IMHB1.

The interactions between the pathogen and host were analyzed against the PHI database, indicating that 18 proteins have experimentally demonstrated effects on the pathogenicity of Brucella, four proteins have no reported impact (Table 6), and four proteins have roles in virulence that remain controversial. All experimental evidence was derived from studies employing Mus musculus as the host.

Table 6

Table 6. Predicted interaction between Brucella melitensis strain IMHB1 and host.

4 Discussion

Although brucellosis is a recognized zoonotic disease, the functional genomic characteristics of Brucella strains in specific regions remains poorly characterized, hindering the development of targeted public health control measures. In 2002, the genome of B. melitensis was sequenced for the first time using the shotgun approach (DelVecchio et al., 2002). However, few reports exist on the genomic characteristics of Brucella in Hulunbuir, Inner Mongolia, China. We previously reported the molecular epidemiological characteristics of 20 B. melitensis strains associated with arthritis in Hulunbuir based on Illumina NovaSeq sequencing data (Zhu et al., 2024). The complete genomic structure and functional characteristics of B. melitensis from Hulunbuir, based on Oxford Nanopore sequencing technology, were reported for the first time.

In this study, a B. melitensis strain IMHB1 was isolated from the blood of a patient with brucellosis. Genome sequencing revealing two chromosomes, totaling 3.32 Mbp, with no plasmid detected. The GC content of this genome was 57.22%, and 3152 coding genes were predicted, covering 86.55% of the genome. Of these, 94.26% were functionally annotated in the eggNOG database, showing high consistency with B. melitensis 16M. Previous studies have demonstrated that the highly conserved genome of Brucella represents a stable adaptive strategy evolved through long-term association with its natural hosts (Salmon-Divon et al., 2018a; Salmon-Divon et al., 2018b). The absence of significant mutations in the clinical isolates suggests that large-scale genomic recombination is not a prerequisite for cross-species transmission. Correspondingly, the prediction of highly conserved virulence factors indicates that Brucella employs similar mechanisms for intracellular survival, immune evasion, and pathogenesis in diverse hosts (Moreno, 2014; Celli, 2019). This genomic stability may contribute to the persistent challenge of brucellosis as a zoonotic disease.

The PHASTEST database predicted an intact prophage genome (15.2 kb) in B. melitensis IMHB1, whereas a shorter prophage region (11.7 kb) was identified in B. melitensis 16M. This variation provides evolutionary evidence for historical genetic recombination between bacteriophages and Brucella. PhoP in the prophage genome and phoQ in the Brucella genome are tandemly arranged and constitute a two-component system (TCS). PhoQ senses Mg²⁺, cationic antimicrobial peptides, and short-chain fatty acids via autophosphorylation, activating the transcription factor PhoP. Phosphorylated PhoP regulates gene expression to enhance bacterial resistance to antimicrobial agents and nutrient stress (Montagne et al., 2001; Groisman et al., 2021).

Currently, research on the PhoQ/PhoP TSC has predominantly focused on Enterobacteriaceae, with few reports in Brucella. The prediction that a prophage-integrated PhoQ/PhoP TCS enhances bacterial resistance remains computationally unconfirmed. Therefore, future studies employing RNA-seq and gene knockout techniques are essential to validate the co-expression of this system and elucidate its impact on Brucella virulence.

Under strict RGI matching, the resistance gene mprF was identified with high confidence. MprF is a large membrane protein that modifies the anionic phospholipid phosphatidylglycerol on the membrane surface, thereby reducing the affinity for cationic antimicrobial peptides, such as defensin, and conferring resistance to innate host defenses and cationic antibiotics (Ernst et al., 2009). An antibody has been reported to block the physiological function of MprF, rendering MRSA sensitive to cationic antimicrobial peptides and antibiotics and reducing MRSA survival in human phagocytes (Slavetinsky et al., 2022). The functional blockade of mprF may be a novel strategy for the clinical treatment of brucellosis.

The three additional putative resistance genes identified in the IMHB1 strain exhibited <60% sequence identity with their reference sequences in the CARD database. This level of homology is generally considered insufficient to confer a definitive resistance phenotype. Nonetheless, the detection of these homologs implies the presence of evolutionarily related sequences within the genome, which may represent divergent resistance genes, pseudogenes, or ancestral genetic elements that have not acquired full resistance capability (Alcock et al., 2023). As these predictions are based solely on protein homology, future studies employing functional validation, such as gene expression profiling under antibiotic stress or cloning coupled with heterologous expression, are essential to elucidate their potential role in antimicrobial resistance.

Although our study provides a comprehensive genomic characterization of B. melitensis IMHB1 to elucidate its potential functions, some limitations should be acknowledged. The primary limitation is its in silico and predictive nature. All genomic features and functional analyses were based on DNA or protein sequence homology. Therefore, these predictions require subsequent in vitro and in vivo experimental validation to confirm their functional expression and biological significance during actual infection. On the other hand, the findings from a single clinical isolate, although insightful, are limited in their broader applicability. Specific genomic variations, such as those distinguishing it from the B. melitensis 16M strain, may represent singular occurrences rather than patterns common across Brucella spp.

Despite these limitations, the genomic insights garnered from this study establish a critical foundation for several pivotal research avenues. The genomic conservation observed in Brucella suggests that the core mechanisms underlying intracellular survival, replication, immune evasion, and pathogenesis may be shared across species and hosts. To fully decipher this pathogenic blueprint, future studies should prioritize large-scale pan-genome and comparative genomic analyses. Such efforts will be instrumental in refining the phylogeny of Brucella, identifying genuine genetic markers of tissue tropism and disease severity, and distinguishing the stable core genomes from the dynamic accessory genomes. Furthermore, to bridge the gap between genomic potential and functional reality, it is essential to integrate transcriptomic and proteomic data from bacteria cultured under conditions that mimic intracellular niches. This multi-omics approach will unequivocally reveal the pathways actively employed during infection. Addressing these gaps will move beyond genomic prediction toward a mechanistic understanding of brucellosis pathogenesis and facilitate the development of novel diagnostic and therapeutic strategies.

5 Conclusion

In summary, this study presents a complete genome map of B. melitensis biotype III strain IMHB1, closely related to cgST-588, a clinical isolate from China. The multi-faceted genomic characterization delineated its architecture, comprising two circular chromosomes (2.13 Mbp and 1.19 Mbp), and identified key genetic elements, including 121 MGEs, 36 putative HGT regions, and a prophage region. Functional annotation further revealed 10 genomic islands, 45 CAZymes, three BGCs, and four antibiotic resistance genes, along with annotation in 20 eggNOG categories and 252 KEGG pathways. Notably, 66 virulence factors were identified, including 18 proteins with experimentally verified roles in pathogen-host interactions. Collectively, these findings provide a valuable genomic resource and multilayered insights into B. melitensis, which will support future studies aimed at improving the diagnosis and treatment of brucellosis.

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/, CP195256-CP195257.

Ethics statement

The studies involving humans were approved by The ethics committee of Hulunbuir People’s Hospital. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

XZ: Conceptualization, Writing – original draft, Writing – review & editing. CL: Writing – original draft. LS: Data curation, Writing – review & editing. CfL: Data curation, Writing – review & editing. RY: Software, Writing – review & editing. LP: Investigation, Writing – review & editing. YL: Investigation, Writing – review & editing. SL: Conceptualization, Writing – review & editing. XL: Conceptualization, Writing – review & editing.

Funding

The author(s) declare financial support was received for the research and/or publication of this article. This work was supported by the National Natural Science Foundation of China [Grant No. 82160632], the Science and Technology Program of the Joint Fund of Scientific Research for the Public Hospitals of Inner Mongolia Academy of Medical Sciences [Grant No. 2024GLLH0822], and the Fundamental Research and Applied Fundamental Research Project of Hulunbuir [Grant No. GH2024003].

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that no Generative AI was used in the creation of this manuscript.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcimb.2025.1653521/full#supplementary-material

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