Introduction

The genus Micromonospora was proposed by Ørskov1. At the time of writing, based on Parte2 the genus Micromonospora includes 130 species with validly published names (https://lpsn.dsmz.de/genus/micromonospora), widely distributed in various environments, including peat swamp forests3 root noduless4 hot spring soils5 and deep sea environments6. The Micromonospora belongs to the actinomycetes (phylum Actinomycetota). Members of this genus are aerobic, Gram-stain-positive, and characterised by a high G + C content. They lack aerial spores, nonmotile spores on an extensively branched substrate mycelium. This initial description was later emended by Nouioui et al.7. The genus produces either xylose or mannose or galactose and glucose as major sugars. Hydrolysates of these microorganisms are rich in meso- and/or 3-OH-diaminopimelic acid (3-OH-A2pm) with phosphatidylethanolamine being a diagnostic polar lipid. Iso-C15:0 and iso-C16:0 are the predominant fatty acids6,7,8,9.

Recently, phylogenetic methodologies that harness whole-genome sequence-based metrics have risen to prominence as indispensable tools for the classification of prokaryotic taxa10,11. Phylogenomic analyses of the core genome, coupled with Overall Genomic Relatedness Indices (OGRIs), including ANI, dDDH, and AAI12,13 provide comprehensive and nuanced understanding of genetic relationships that are not attainable through the utilization of phenotypic characteristics, chemotaxonomic assessments, or single-gene markers like the traditional 16S rRNA gene method. These advanced techniques have been extensively utilized in the reclassification of numerous bacterial taxa. These advanced methodologies enable scientists to align taxonomic classifications more precisely with phylogenetic affiliations14,15.

Micromonospora veneta DSM 109713T (=CAP 181T =NRRLB-65535T) was isolated from a surface sterilized root sample of a native pine tree, Flinders University, Adelaide, South Australia16 and was validated in the IJSEM (Validation list no. 203). Micromonospora coerulea JCM 3175T (=ATCC 27008T =DSM 43143T =IFO 13504T =KCTC 9368T =NBRC 13504T =VKMAc-661T) was first reported by Jensen17 was isolated from Hawaiian soil18 and was validated in the IJSEM19. Through detailed phylogenomic analysis and the Overall Genomic Relatedness Indices (OGRIs), we observed that M. veneta DSM 109713T exhibited significant genomic similarity resembling M. coerulea JCM 3175T. During our analysis based on genomic data, we observed that M. veneta DSM 109713T and M. coerulea JCM 3175T exhibited similar characteristics. Consequently, we clarify the relationship between M. veneta DSM 109713T and M. coerulea JCM 3175T utilizing genomics-based methods. By elucidating the taxonomic relationships within the genus Micromonospora, this study enhances our understanding of the diversity and distribution of these bacteria with greater precision.

Materials and methods

Genomic dataset

M. veneta DSM 109713T and M. coerulea JCM 3175T shared a 99.2% similarity with their 16S rRNA gene sequences, indicating that they might represent the same species. we conducted an exhaustive analysis that encompassed phylogenomic and pan-genomic evaluations, coupled with a comparative assessment of phenotypic characteristics, in order to elucidate the intricate relationship between M. veneta DSM 109713T and M. coerulea JCM 3175T. This study re-evaluated their taxonomic relationship.

The 16S rRNA gene sequence identity between M. veneta DSM 109713T and M. coerulea JCM 3175T was compared using the pairwise alignment feature implemented on the EzBioCloud server (https://www.ezbiocloud.net/tools/pairAlign). By utilizing the BLAST feature of the National Center for Biotechnology Information (https://www.ncbi.nlm.nih.gov/), the 16S rRNA gene sequences can be extracted from the genomes of strains DSM 109713T and JCM 3175T. The 16S rRNA gene sequences of closely related type strains were downloaded from EzBioCloud server at (https://www.ezbiocloud.net/)20. Genome sequences and related genomic information of the tested strains were obtained from the NCBI Genome Portal (https://www.ncbi.nlm.nih.gov/datasets/genome/?taxon=1873). To guarantee the quality of the data, the retrieved genomes were assessed for their completeness and contamination levels using the CheckM tool21. The genomic information of the relevant strains, including integrity and contamination rate, is provided in Table 1.

Table 1 Genomic datasets used in this study. “A.” stands for Actinoplanes.
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Phylogenetic analysis

Phylogenetic trees were reconstructed using the maximum-likelihood (ML) statistical method employing MEGA-1122. The maximum-likelihood trees were reconstructed using Kimura’s two-parameter model, transitions + transversions, uniform rates and complete deletion options with bootstrap values based on 1000 replicates23.

Phylogenomic and overall genome relatedness indices

The draft genome sequences of M. coerulea JCM 3175T (BAABGU000000000) and M. veneta DSM 109713T (JAEMUW000000000) were downloaded from the NCBI database. For phylogenomic analysis, the genome sequence data were uploaded to the Type (Strain) Genome Server (TYGS) (https://tygs.dsmz.de)24, incorporating recent updates and features introduced by Meier-Kolthoff et al.25.

The average amino acid identity (AAI) was measured with an online calculator(http://enve-omics.ce.gatech.edu/aai). The average nucleotide identity (ANI) between two genomes was calculated with pairwise genome alignment using the ANI-BLAST (ANIb) and ANI-MUMmer (ANIm) algorithms implemented within the JSpeciesWS web service as described by Richter & Rosselló-Móra12. The digital DNA–DNA hybridization (dDDH) estimate value was analyzed using the genome-to-genome distance calculator (GGDC)12,26,27 ‚28. The contig files were uploaded to the GGDC 3.0 Web server (https://ggdc.dsmz.de/ggdc.php#) for dDDH calculations based on formula 2 (identities/HSP length). Furthermore, a comparison was conducted among the two strains in terms of their phenotypic characteristics, as well as their biochemical and chemotaxonomic properties (Table 2).

Table 2 Differential characteristics between M. veneta DSM 109713T and M. coerulea JCM 3175T.
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Pangenomic analysis

To assess genomic structure and variations within the two strains and closely related Micromonospora species, the Integrated Prokaryotes Genome and Pan-genome Analysis (IPGA) web server (https://nmdc.cn/ipga)28‚29 and the OrthoVenn3 web server (https://orthovenn3.bioinfotoolkits.net/home), (accessed on December 17 2024) was used, applying a minimum sequence identity threshold of 70% with default settings.

Results and discussion

Phylogenetic analysis

The results from the blast analysis indicated a 99.2% similarity between M. veneta DSM 109713T and M. coerulea JCM 3175T. The phylogenetic trees indicate that M. veneta DSM 109713T and M. coerulea JCM 3175T formed a tight cluster within the genus Micromonospora (Fig. 1). The significant similarity noted between M. veneta DSM 109713T and M. coerulea JCM 3175T indicates a highly intimate evolutionary connection.

Fig. 1
figure 1

The length of the 16S rRNA gene sequences of M. coerulea JCM 3175T and M. veneta DSM 109713T are 1,436 bp and 1,438 bp respectively. Maximum-likelihood tree based on 16S rRNA gene sequences, showing the phylogenetic positions of strains DSM 109713T and JCM 3175T and related members within the genus Micromonospora. Actinoplanes aksuensis TRM 88003T (OM 112204) was used as an outgroup. Bootstrap values (expressed as percentages of 1000 replicates) above 50% are shown at the branch points. Bar, 0.01 substitutions per nucleotide position.

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Phylogenomic and overall genome relatedness indices

The results show that M. veneta DSM 109713T and M. coerulea JCM 3175T form a tight cluster within the genus Micromonospora (Fig. 2).

Fig. 2
figure 2

Whole-genome based phylogenomic tree reconstructed using the Type (Strain) Genome Server (TYGS) showing the phylogenomic relationship of strain DSM 109713T and JCM 3175T and related members. The branch lengths are scaled in terms of Genome BLAST Distance Phylogeny approach (GBDP) distance formula d5. The numbers above branches are GBDP pseudo-bootstrap support values > 50% from 100 replicates, with an average branch support of 50.7%. The tree was rooted at the midpoint.

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The 97.57% AAI value between M. veneta DSM 109713T and M. coerulea JCM 3175T was above the threshold value (95.5%) for the delineation of prokaryotic species29‚30. The values of ANIb and ANIm of M. veneta DSM 109713T and M. coerulea JCM 3175T were 97.81% and 98.40% respectively, which was above the threshold value for delineating species (95–96%)25‚26. The dDDH estimate value between M. veneta DSM 109713T and M. coerulea JCM 3175T was 85.0 ± 2.6%, above the threshold value (70%) for the delineation of prokaryotic species29‚30. The genomic DNA G + C contents of M. veneta DSM 109713T and M. coerulea JCM 3175T were 72.5% and 72.5%, and these results strongly support the hypothesis that the two strains represent a single species. AAI, ANIb and dDDH values between M. veneta DSM 109713T and M. coerulea JCM 3175T and closely related type strains are given in Table 3.

Table 3 AAI, ANI and dDDH values between M. veneta DSM 109713T and M. coerulea JCM 3175T and closely related type strains.
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Pangenomic analysis and comparison of phenotypic and chemotaxonomic features

A pangenome analysis was conducted to discern the shared and unique functional attributes among the two strains and their affiliated taxa. Utilizing the IPGA tool, orthologous genes derived from seventeen selected genomes were systematically classified into core, accessory, and unique gene clusters, as illustrated in Fig. 3. After pooling genomes using Roary, a total of 28,410 orthologous genes were identified. Out of these, there are 1928 core gene clusters, predominantly encompassing genes related to metabolic enzymes, information storage, cellular processes, and signaling mechanisms30‚31 (Fig. 3A). The vast majority were classified as unique gene clusters that were specific to individual genomes. The results obtained from the pan-genome analysis concurred with those derived from our phylogenomic analyses, thereby bolstering the notion of a close genetic kinship among these strains through two mutually reinforcing methodologies.

Fig. 3
figure 3

Pangenome analysis of the 16 Micromonospora type strains. (A) A pangenome map depicting the functional distribution of core gene clusters and unique genes in the selected Micromonospora genomes. (B) The accumulative curve showing the number of core gene clusters in relation to the number of genomes included in the pangenome analysis. The blue line represents the change in number of core gene clusters as the number of genomes included in the pan-genome analysis increases. The orange line typically indicates the number of non-core gene clusters (or gene clusters, variable gene clusters) as the number of genomes included changes. (C) UpSet plot illustrating the unique genes as well as the genes shared between the Micromonospora strains.

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The OrthoVenn3 web server with default parameters (E-value 1 × 10–5, inflation value 1.5) was used to identify orthologous gene clusters between M. veneta DSM 109713T and M. coerulea JCM 3175T both strains shared 5365 out of 5448 clusters. This gene distribution offers insights into potential functional diversity and evolutionary relationships among the two strains (Fig. 4). Additionally, M. veneta DSM 109713T and M. coerulea JCM 3175T have 51 and 32 unique genes, respectively that may contribute to traits unique to specific strains31‚32.

Fig. 4
figure 4

Venn diagram representing the subgroups of a pan-genome of the two strains (M. veneta DSM 109713T and M. coerulea JCM 3175T).

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This conclusion was bolstered further by a comparative analysis of phenotypic and chemotaxonomic characteristics between the two strains. According to the articles of Kaewkla O and Nimaichand S, except for the difference in utilization of mannitol and trehalose (as sole carbon sources) and individual quinones, M. veneta DSM 109713T and M. coerulea JCM 3175T showed almost the same results as follows: both positive for fructose, D-galactose, myo-inositol and raffinose, both negative for L-arabinose, cellulose, malate, aerial hyphae. Starch is hydrolyzed, but not L-tyrosine. The major cellular fatty acids of M. veneta DSM 109713T and M. coerulea JCM 3175T were identified as iso-C16:0 and iso-C15:016,33‚34. Therefore, the phenotypic and chemotaxonomic characteristics of M. veneta DSM 109713T and M. coerulea JCM 3175T further support this conclusion that Micromonospora veneta Kaewkla et al. 2022 is a later heterotypic synonym of Micromonospora coerulea Jensen 1932 (Approved Lists 1980).

Conclusion

Based on genomic, pan-genome analysis, phylogenetic and chemotaxonomic results, we propose that Micromonospora veneta should be reclassified as a later heterotypic synonym of Micromonospora coerulea.

Emended description of Micromonospora coerulea Jensen 1932 (Approved lists 1980)

The description aligns with the original reports by Hirsch et al.18 Kaewkla et al.16 and Nimaichand et al.33 with the following additional features: The growth occurs at temperature 24–37°C, salinity 0–3% NaCl (w/v), growth occurs between pH 6.0 and 8.0 (optimum 7.0). Can utilize adonitol, cellobiose, dulcitol, fructose, galactose, inositol, lactose, maltose, mannitol, melibiose, raffinose as a single carbon source. Produces acid from fructose, galactose, myo-inositol, mannitol, raffinose. Can hydrolyze skim milk and starch. In the assimilation of organic acids and citrate is weakly positive, malate is negative. The predominant menaquinone is MK-9(H4) or MK-10. The major main fatty acids were iso-C16:0 and iso-C15:0. The genome size of the type strain is 6.6 Mb. The DNA G + C content of the type strain JCM 3175T (=ATCC 27008T =DSM 43143T =IFO 13504T =KCTC 9368T =NBRC 13504T =VKMAc-661T) is 72.84%. The accession numbers of the whole genome and the 16S rRNA gene sequences of the type strain are GCA_039541735.1 and NR_026277.1, respectively.