Abstract
Objective
Rummeliibacillus, a genus encompassing three known species, R. stabekisii, R. pycnus, and R. suwonensis, has a wide range of potential applications in biodegradation, probiotics, animal feed, and production of arginine, caproic acid, and other compounds. This study aims to explore the genetic diversity of this genus at the genomic level.
Methods
A comparative pangenome analysis of 12 strains isolated from different sources was conducted. In addition, the phylogenetic analysis, functional annotation, genomic metabolic pathway analysis, and prediction of mobile genetic elements were carried out.
Results
A total of 8 024 gene clusters were identified. The core genome, accessory genome, and strain-specific genes comprised 1 550, 3 941, and 2 533 gene clusters, respectively. In the core genome, the arginine cycle of six strains was complete. Seven strains had the ability to completely biosynthesize acetoin. However, only R. pycnus and R. suwonensis 3B-1 were able to completely biosynthesize caproic acid. The phylogenetic tree, DNA-DNA hybridization, and average nucleotide identity showed that Rummeliibacillus sp. G93 and Rummeliibacillus sp. TYF-LIM-RU47 were strains of R. stabekisii. Rummeliibacillus sp. POC4 and Rummeliibacillus sp. TYF005 may belong to a new species of this genus. In addition, genomic islands were identified in all the 12 strains, with the number ranging from four (R. stabekisii DSM 25578 and R. stabekisii NBRC 104870) to 14 (Rummeliibacillus sp. SL167 and Rummeliibacillus sp. TYF005), and prophage sequences were found in five of the 12 strains.
Conclusion
This study provides a genomic framework for Rummeliibacillus that could assist the further exploration of this genus.
Rummeliibacillus was first described in the United States in 200
Now, the availability of next-generation sequencing technologies and decreasing sequencing costs have allowed genome-wide approaches for microbial analysi
In this study, we systematically studied the specific taxonomic status of Rummeliibacillus sp. through average nucleotide identity (ANI), DNA-DNA hybridization (DDH), and phylogenetic tree analyses. Meanwhile, we analyzed the characteristics of the pangenome, core genes, and accessory genes of Rummeliibacillus sp. and evaluated the phylogenetic relationship of Rummeliibacillus sp. at the genome level. To study the potential functional characteristics of Rummeliibacillus sp., the metabolic capacity of the core genome and the accessory genome were analyzed. We evaluated genomic plasticity and genome evolution by the analysis of mobile genetic elements (MGEs
1 Materials and Methods
1.1 Pangenome analysis
The 12 genomes of Rummeliibacillus sp. used for the pangenome analysis were downloaded from the FTP site of the Reference Sequence (RefSeq) database at NCBI (ftp://ftp.ncbi.nih.gov/genomes/, accessed on March 4, 2023). Once the download was complete, we assessed of the completeness and contamination of these 12 genomes using CheckM (https://github.com/Ecogenomics/CheckM; Table S1, the data has been submitted to the National Microbiology Data Center, with the registration number: NMDCX0001747). The detailed genomic information is shown in
Strain | Country | Source | Size (Mb) | G+C content (%) | Proteins | Scaffolds | Accession number |
---|---|---|---|---|---|---|---|
DSM 15030 | Germany | Soil | 3.85 | 34.60 | 3 554 | 1 | GCA_002884495.1 |
G20 | Korea | Soil | 4.11 | 35.90 | 3 638 | 16 | GCA_007896435.1 |
3B-1 | China | Pit mud | 4.12 | 35.90 | 3 530 | 83 | GCA_017578305.1 |
G93 | China | Soil | 3.24 | 37.70 | 3 121 | 1 | GCA_023515935.1 |
POC4 | Poland | Sewage sludge | 3.69 | 34.50 | 3 570 | 163 | GCA_003576525.1 |
SL167 | Korea | Soil | 4.17 | 35.80 | 3 757 | 14 | GCA_007896505.1 |
TYF-LIM-RU47 | China | Vinegar | 3.30 | 37.40 | 3 273 | 14 | GCA_008638315.1 |
TYF005 | China | Vinegar | 3.70 | 34.40 | 3 564 | 117 | GCA_003844195.1 |
NBRC 104870 | USA | Missing | 3.26 | 37.30 | 3 150 | 23 | GCA_007988965.1 |
PP9 | Antarctica | Soil | 3.42 | 37.69 | 3 334 | 2 | GCA_001617605.1 |
DSM 25578 | Missing | Missing | 3.28 | 37.30 | 3 105 | 12 | GCA_014202625.1 |
MER TA 13 | USA | Missing | 3.35 | 37.40 | 3 257 | 68 | GCA_023713565.1 |
1.2 Phylogenetic analysis
For the phylogenomic analysis, whole-genome sequences of Rummeliibacillus sp. strains were compared by computing the ANI (two strains are considered to belong to the same species if the ANI is greater than 95%
1.3 Functional annotation of the pangenome
Clusters of orthologous groups (COGs) of annotated proteins were generated using eggNOG-mapper to assign genes to COG categorie
2 Results and Discussion
2.1 Pangenome and core genome of Rummeliibacillus sp.
A total of 12 Rummeliibacillus sp. genomes were used for the pangenome analysis. Genome sizes ranged from 3.24 to 4.17 Mb. The average number of protein-coding genes was 3 404, and the G+C content ranged from 34.40% to 37.70% (

Figure 1 Pangenome of Rummeliibacillus sp. core and accessory genome sizes and the number of specific genes in each Rummeliibacillus sp. strain. The same color for a specific gene represents the same species of bacteria.
Analysis of the existence of open and closed genomes can now be performed in many genera as the result of the burgeoning increase in microbial genome sequences from different strains within the same genu

Figure 2 Development of pangenome and core genome sizes for Rummeliibacillus sp. strains with genome number varying from 1 to 12. The cumulative curve (in orange) supports an open pangenome.
2.2 Phylogenetic analysis of Rummeliibacillus sp.
A comparison of the ANI between unknown genera and known species was performed using JSpeciesW

Figure 3 Comparison of the average nucleotide identity (ANI) values between the genomes of the 12 Rummeliibacillus sp. strains. A: Heatmaps display the ANI values between the 12 Rummeliibacillus sp. strains. The color represents the identity of strains, with purple indicating lower ANI values and red indicating higher ANI values. Color bars above and to the right of the heatmaps correspond to the source of each Rummeliibacillus sp. isolate. B: Phylogenetic trees of Rummeliibacillus sp. strains based on the core genome.
2.3 COG functional annotation of Rummeliibacillus sp. genes
COG analysis of pan-genomic gene clusters was conducted. Unknown function (S) was the largest category of the core genome, accessory genome, and strain-specific genes, accounting for 26.7%, 22.3%, and 29.8%, respectively (

Figure 4 Distribution of COG categories between the core genome, accessory genome, and strain-specific genes of Rummeliibacillus sp. strains. A: RNA processing and modification; B: Chromatin structure and dynamics; C: Energy production and conversion; D: Cell cycle control, cell division, chromosome partitioning; E: Amino acid transport and metabolism; F: Nucleotide transport and metabolism; G: Carbohydrate transport and metabolism; H: Coenzyme transport and metabolism; I: Lipid transport and metabolism; J: Translation, ribosomal structure, and biogenesis; K: Transcription; L: Replication, recombination, and repair; M: Cell wall/membrane/envelope biogenesis; N: Cell motility; O: Posttranslational modification, protein turnover, chaperones; P: Inorganic ion transport and metabolism; Q: Secondary metabolite biosynthesis, transport, and catabolism; S: Function unknown; T: Signal transduction mechanisms; U: Intracellular trafficking, secretion, and vesicular transport; V: Defense mechanisms; W: Extracellular structures.
2.4 Genomic metabolic pathway analysis of Rummeliibacillus sp.
The KAAS annotation showed that all the 1 550 core gene clusters (19.3%) were assigned with KO numbers. The most annotated gene families in the core genome belong to carbohydrate metabolism. For substrate transport, ATP-binding cassette (ABC) transporters and phosphotransferase systems (PTSs) were the main transporting systems annotated by KAAS. The number of genes distributed in metabolic pathways is shown in Table S2 (The data has been submitted to the National Microbiology Data Center, with the registration number: NMDCX0001748). In the carbohydrate metabolism pathway, 138 genes are annotated in the core genome, 195 genes are annotated in the accessory genome, and 54 genes are annotated in the specific genome.
2.4.1 Caproic acid and acetoin metabolism
In this study, the pathways involved in the KEGG pathway caproic acid and acetoin metabolism were constructed in Rummeliibacillus sp. Some glycolysis genes can be found in the core genome, and the missing genes ptsG and pgi exist in the accessory genome (R. pycnus, Rummeliibacillus sp. POC4, Rummeliibacillus sp. SL167, Rummeliibacillus sp. TYF005, R. suwonensis 3B-1, and R. suwonensis G20).

Figure 5 Overview of caproic acid, arginine, and sulfur metabolism in Rummeliibacillus sp. strains and distribution of accessory genome genes. A: Assimilatory sulfate reduction and main carbon metabolism annotated in the pangenome of Rummeliibacillus sp. strains; B: Genes annotated in caproic acid fermentation and metabolism of acetoin. Genes shared by all the 12 genomes (core genome) are shown in red, and genes in the accessory genome are shown in green; C: Distribution of genes involved in arginine metabolism; D: The distribution of genes in the accessory genome among different strains (blue represents the presence of the gene, while orange represents the absence of the gene).
In addition, the caproic acid biosynthesis pathway showed that most caproic acid synthesis genes were present in the core genome, but the bcd gene is found only in R. pycnus and R. suwonensis 3B-1 (
2.4.2 Arginine metabolism
Amino acid metabolism is another important metabolic pathway, with 126, 229 and 58 genes annotated to the core genome, accessory genome, and specific genome, respectively, of this genus.
2.4.3 Assimilatory sulfate reduction
In the accessory genome, the gene set for assimilatory sulfate reduction is complete in strains such as 3B-1, POC4, and G20 (Figure
2.5 Virulence factor analysis
The sequences of the core genome, the accessory genome, and the specific genome were compared with the VFDB database. In the Rummeliibacillus sp. pangenome, 38 virulence genes were identified in total. Of these, 13 core virulence genes were shared by all strains and four unique virulence factors were present in one strain each (Table S3, the data has been submitted to the National Microbiology Data Center, with the registration number: NMDCX0001749). Rummeliibacillus sp. SL167 (from soil) had the highest number of virulence genes (32), and R. pycnus (from soil) had the lowest number of virulence genes (19). The genomes of all 12 Rummeliibacillus sp. strains harbor genes encoding virulence factors, which are involved in processes including adhesion (flmH and slrA), secretion (clpB and cdsN), regulation (cheY and lisR), and motility (fliQ). Adhesion-related genes can promote adhesion and biofilm formation, which is an important factor in the pathogenesis of Streptococcu
2.6 Prediction of MGEs
To study the MGEs in Rummeliibacillus sp., we used IslandViewer 4 (an integrated interface for computational identification and visualization of GIs). MGEs can mediate the acquisition of DNA and promote the expansion of the gene pool of bacterial group
In addition, the genomes of Rummeliibacillus sp. in this study were scanned using the PHASTER online service to obtain phage sequence
Strain | Intact | Questionable | Incomplete |
---|---|---|---|
Rummeliibacillus pycnus DSM 15030 | 0 | 1 | 0 |
Rummeliibacillus suwonensis G20 | 0 | 1 | 2 |
Rummeliibacillus suwonensis 3B-1 | 0 | 0 | 2 |
Rummeliibacillus sp. G93 | 1 | 0 | 0 |
Rummeliibacillus sp. POC4 | 0 | 2 | 4 |
Rummeliibacillus sp. SL167 | 1 | 0 | 2 |
Rummeliibacillus sp. TYF-LIM-RU47 | 2 | 1 | 4 |
Rummeliibacillus sp. TYF005 | 1 | 0 | 1 |
Rummeliibacillus stabekisii NBRC 104870 | 0 | 0 | 4 |
Rummeliibacillus stabekisii PP9 | 3 | 1 | 1 |
Rummeliibacillus stabekisii DSM 25578 | 0 | 0 | 4 |
Rummeliibacillus stabekisii MER TA 13 | 0 | 2 | 2 |
Strain | Region length (kb) | Total proteins | Most common phage (NCBI accession) | G+C content (%) |
---|---|---|---|---|
R. pycnus DSM 15030 | 37.4 | 23 | PHAGE_Staphy_6ec (NC_024355) | 31.75 |
R. suwonensis G20 | 50.3 | 43 | PHAGE_Lister_LP_101 (NC_024387) | 31.07 |
Rummeliibacillus sp. G93 | 43.9 | 78 | PHAGE_Aeriba_AP45 (NC_048651) | 36.52 |
Rummeliibacillus sp. POC4 | 35.1 | 58 | PHAGE_Bacill_phBC6A52 (NC_004821) | 33.71 |
Rummeliibacillus sp. POC4 | 18.6 | 25 | PHAGE_Bacill_SPP1 (NC_004166) | 36.28 |
Rummeliibacillus sp. SL167 | 55.5 | 37 | PHAGE_Geobac_GBK2 (NC_023612) | 42.43 |
Rummeliibacillus sp. TYF-LIM-RU47 | 24.7 | 44 | PHAGE_Aeriba_AP45 (NC_048651) | 36.96 |
Rummeliibacillus sp. TYF-LIM-RU47 | 34.3 | 52 | PHAGE_Lister_B054 (NC_009813) | 37.10 |
Rummeliibacillus sp. TYF005 | 49.0 | 72 | PHAGE_Bacill_1 (NC_009737) | 33.43 |
R. stabekisii PP9 | 54.2 | 78 | PHAGE_Paenib_Vegas (NC_028767) | 36.81 |
R. stabekisii PP9 | 47.0 | 63 | PHAGE_Paenib_Vegas (NC_028767) | 36.85 |
R. stabekisii PP9 | 44.9 | 75 | PHAGE_Aeriba_AP45 (NC_048651) | 37.01 |
R. stabekisii MER TA 13 | 17.4 | 20 | PHAGE_Bacill_SPP1 (NC_004166) | 38.77 |
R. stabekisii MER TA 13 | 31.9 | 23 | PHAGE_Paenib_Vegas (NC_028767) | 34.24 |
3 Conclusions
This work represents the first characterization of Rummeliibacillus species using pan-genomic analysis. The pangenome of Rummeliibacillus sp. strains is open, and the addition of newly sequenced genomes could increase the number of genes and the size of the pangenome. The pathway for arginine metabolism was discovered in all 12 Rummeliibacillus sp. strains, and only two strains had the ability to completely metabolize caproic acid, while seven strains had the ability to completely biosynthesize acetoin. Additionally, a complete assimilation sulfate reduction process was found in six strains. MGEs, including bacteriophages and GIs, were detected in the pangenome of Rummeliibacillus sp., which might give rise to horizontal gene transfer for environmental adaptation and increased genome diversity of Rummeliibacillus sp. This study provides insights for future research on the genetics and practical application of Rummeliibacillus sp.
Contributions Statement
ZOU Wei: Conceptualization, formal analysis, supervision, methodology, writing–review & editing. YANG Lingling: Formal analysis, visualization, writing–review & editing. LIU Chaojie: Methodology, formal analysis, visualization, writing–original draft preparation, data curation. ZHENG Jia: validation. ZHANG Kaizheng: Investigation. QIAO Zongwei: Investigation.
Acknowledgements
We thank International Science Editing (http://www.internationalscienceediting.com) for editing this manuscript.
Conflict of Interest
The authors declare that there is no conflict of interest.
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