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References

  1. Ding L, Yokota A. 2004. Proposals of Curvibacter gracilis gen. nov., sp. nov. and Herbaspirillum putei sp. nov. for bacterial strains isolated from well water and reclassification of [Pseudomonas] huttiensis, [Pseudomonas] lanceolata, [Aquaspirillum] delicatum and [Aquaspirillum] autotrophicum as Herbaspirillum huttiense comb. nov., Curvibacter lanceolatus comb. nov., Curvibacter delicatus comb. nov. and Herbaspirillum autotrophicum comb. nov. . Int. J. Syst. Evol. Microbiol. 54: 2223-2230.
    Pubmed CrossRef
  2. Parte AC, Carbasse JS, Meier-Kolthoff JP, Reimer LC, Göker M. 2020. List of prokaryotic names with standing in nomenclature (LPSN) moves to the DSMZ. Int. J. Syst. Evol. Microbiol. 70: 5607-5612.
    Pubmed PMC CrossRef
  3. Ding L, Yokota A. 2010. Curvibacter fontana sp. nov., a microaerobic bacteria isolated from well water. J. Gen. Appl. Microbiol. 56: 267-271.
    Pubmed CrossRef
  4. Leifson E. 1962. The bacterial flora of distilled and stored water. III. New species of the genera Corynebacterium, Flavobacterium, Spirillum and Pseudomonas. Int. Bull. Bacteriol. Nomencl. Taxon. 12: 161-170.
    CrossRef
  5. Bullerjahn GS, Post AF. 2014. Physiology and molecular biology of aquatic cyanobacteria. Front. Microbiol. 5: 359.
    Pubmed PMC CrossRef
  6. Huisman J, Codd GA, Paerl HW, Ibelings BW, Verspagen JMH, Visser PM. 2018. Cyanobacterial blooms. Nat. Rev. Microbiol. 16: 471-483.
    Pubmed CrossRef
  7. Le VV, Ko SR, Kang M, Lee SA, Oh HM, Ahn CY. 2022. Panacibacter microcysteis sp. nov., isolated from a eutrophic reservoir during the Microcystis bloom period. Arch. Microbiol. 204: 291.
    Pubmed CrossRef
  8. Weisburg WG, Barns SM, Pelletier DA, Lane DJ. 1991. 16S ribosomal DNA amplification for phylogenetic study. J. Bacteriol. 173: 697-703.
    Pubmed PMC CrossRef
  9. Baker GC, Smith JJ, Cowan DA. 2003. Review and re-analysis of domain-specific 16S primers. J. Microbiol. Methods 55: 541-555.
    Pubmed CrossRef
  10. Youssef N, Sheik CS, Krumholz LR, Najar FZ, Roe BA, Elshahed MS. 2009. Comparison of species richness estimates obtained using nearly complete fragments and simulated pyrosequencing-generated fragments in 16S rRNA gene-based environmental surveys. Appl. Environ. Microbiol. 75: 5227-5236.
    Pubmed PMC CrossRef
  11. Yoon SH, Ha SM, Kwon S, Lim J, Kim Y, Seo H, et al. 2017. Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies. Int. J. Syst. Evol. Microbiol. 67: 1613-1617.
    Pubmed PMC CrossRef
  12. Kanehisa M, Sato Y, Morishima K. 2016. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J. Mol. Biol. 428: 726-731.
    Pubmed CrossRef
  13. Dieckmann MA, Beyvers S, Nkouamedjo-Fankep RC, Hanel PHG, Jelonek L, Blom J, et al. 2021. EDGAR3.0: comparative genomics and phylogenomics on a scalable infrastructure. Nucleic Acids Res. 49: W185-W192.
    Pubmed PMC CrossRef
  14. Blin K, Shaw S, Steinke K, Villebro R, Ziemert N, Lee SY, et al. 2019. AntiSMASH 5.0: updates to the secondary metabolite genome mining pipeline. Nucleic Acids Res. 47: W81-W87.
    Pubmed PMC CrossRef
  15. Felsenstein J. 1981. Evolutionary trees from DNA sequences: a maximum likelihood approach. J. Mol. Evol. 17: 368-376.
    Pubmed CrossRef
  16. Saitou N, Nei M. 1987. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4: 406-425.
  17. Nei M, Kumar S, Takahashi K. 1998. The optimization principle in phylogenetic analysis tends to give incorrect topologies when the number of nucleotides or amino acids used is small. Proc. Natl. Acad. Sci. USA 95: 12390-12397.
    Pubmed PMC CrossRef
  18. Tamura K, Stecher G, Kumar S. 2021. MEGA11: molecular evolutionary genetics analysis version 11. Mol. Biol. Evol. 38: 3022-3027.
    Pubmed PMC CrossRef
  19. Kimura M. 1983. The Neutral Theory of Molecular Evolution. Cambride: Cambridge University Press.
  20. Meier-Kolthoff JP, Auch AF, Klenk HP, Göker M. 2013. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinformatics 14: 60.
    Pubmed PMC CrossRef
  21. Meier-Kolthoff JP, Göker M. 2019. TYGS is an automated high-throughput platform for state-of-the-art genome-based taxonomy. Nat. Commun. 10: 2182.
    Pubmed PMC CrossRef
  22. Skerman VBD. 1967. A Guide to the Identification of the Genera of Bacteria. 2nd edition. The Williams & Wilkins Co.
  23. Smibert RM, Krieg NR. 1994. Phenotypic characterization, pp 607-654, In Gerhardt P, Murray RGE, Wood WA, Krieg NR (eds.), Methods for General and Molecular Bacteriology. American Society for Microbiology, Washington.
  24. Sasser M. 1990. Identification of Bacteria by Gas Chromatography of Cellular Fatty Acids, MIDI Technical Note 101. Newark, DE: MIDI Inc.
  25. Tindall BJ, Sikorski J, Smibert RA, Krieg NR. 2007. Phenotypic characterization and the principles of comparative systematic, pp. 330-393. In Reddy CA, Beveridge TJ, Breznak JA, Marzluf GA, Schmidt TM, Snyder LR (eds.), Methods for General and Molecular Bacteriology. Washington, DC: American Society for Microbiology.
  26. Minnikin DE, O'Donnell AG, Goodfellow M, Alderson G, Athalye M, Schaal A, et al. 1984. An integrated procedure for the extraction of bacterial isoprenoid quinones and polar lipids. J. Microbiol. Methods 2: 233-241.
    CrossRef
  27. Oren A, Duker S, Ritter S. 1996. The polar lipid composition of Walsby's square bacterium. FEMS Microbiol. Lett. 138: 135-140.
    CrossRef
  28. Kates M. 1972. Techniques of Lipidology: Isolation, Analysis and Identification of Lipids. Amsterdam: North-Holland Pub. Co.
  29. Tamaoka J. 1986. Analysis of bacterial menaquinone mixtures by reverse-phase high-performance liquid chromatography. Methods Enzymol. 123: 251-256.
    Pubmed CrossRef
  30. Chun J, Oren A, Ventosa A, Christensen H, Arahal DR, da Costa MS, et al. 2018. Proposed minimal standards for the use of genome data for the taxonomy of prokaryotes. Int. J. Syst. Evol. Microbiol. 68: 461-466.
    Pubmed CrossRef
  31. Luo C, Rodriguez-R LM, Konstantinidis KT. 2014. MyTaxa: an advanced taxonomic classifier for genomic and metagenomic sequences. Nucleic Acids Res. 42: e73.
    Pubmed PMC CrossRef
  32. Qin QL, Xie B Bin, Zhang XY, Chen XL, Zhou BC, Zhou J, et al. 2014. A proposed genus boundary for the prokaryotes based on genomic insights. J. Bacteriol. 196: 2210-2215.
    Pubmed PMC CrossRef
  33. Richter M, Rosselló-Móra R. 2009. Shifting the genomic gold standard for the prokaryotic species definition. Proc. Natl. Acad. Sci. USA 106: 19126-19131.
    Pubmed PMC CrossRef
  34. Auch AF, von Jan M, Klenk HP, Göker M. 2010. Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison. Stand. Genomic Sci. 2: 117-134.
    Pubmed PMC CrossRef
  35. Rouli L, Merhej V, Fournier PE, Raoult D. 2015. The bacterial pangenome as a new tool for analysing pathogenic bacteria. New Microbes New Infect. 7: 72-85.
    Pubmed PMC CrossRef
  36. Park SC, Lee K, Kim YO, Won S, Chun J. 2019. Large-scale genomics reveals the genetic characteristics of seven species and importance of phylogenetic distance for estimating pan-genome size. Front. Microbiol. 10: 834.
    Pubmed PMC CrossRef
  37. Tettelin H, Riley D, Cattuto C, Medini D. 2008. Comparative genomics: the bacterial pan-genome. Curr. Opin. Microbiol. 11: 472-477.
    Pubmed CrossRef
  38. Osbourn A. 2010. Secondary metabolic gene clusters: evolutionary toolkits for chemical innovation. Trends Genet. 26: 449-457.
    Pubmed CrossRef
  39. Oldfield E, Lin FY. 2012. Terpene biosynthesis: modularity rules. Angew. Chem. - Int. Ed. 51: 1124-1137.
    Pubmed PMC CrossRef
  40. Robinson SL, Christenson JK, Wackett LP. 2019. Biosynthesis and chemical diversity of β-lactone natural products. Nat. Prod. Rep. 36: 458-475.
    Pubmed CrossRef
  41. Agrawal S, Acharya D, Adholeya A, Barrow CJ, Deshmukh SK. 2017. Nonribosomal peptides from marine microbes and their antimicrobial and anticancer potential. Front. Pharmacol. 8: 828.
    Pubmed PMC CrossRef
  42. Croft MT, Lawrence AD, Raux-Deery E, Warren MJ, Smith AG. 2005. Algae acquire vitamin B12 through a symbiotic relationship with bacteria. Nature 438: 90-93.
    Pubmed CrossRef
  43. Kim M, Lee J, Yang D, Park HY, Park W. 2020. Seasonal dynamics of the bacterial communities associated with cyanobacterial blooms in the Han River. Environ. Pollut. 266: 115198.
    Pubmed CrossRef
  44. Valderrama JA, Durante-Rodríguez G, Blázquez B, García JL, Carmona M, Díaz E. 2012. Bacterial degradation of benzoate: crossregulation between aerobic and anaerobic pathways. J. Biol. Chem. 287: 10494-10508.
    Pubmed PMC CrossRef
  45. Seo J-S, Keum Y-S, Li Q. 2009. Bacterial degradation of aromatic compounds. Int. J. Environ. Res. Public Health 6: 278-309.
    Pubmed PMC CrossRef
  46. Krieg NR. 1984. Genus Aquaspirillum. Hylemon, Wells, Krieg and Jannasch 1973, 361AL, In Krieg NR, Holt JG (eds.), Bergey’s Manual of Systematic Bacteriology. Baltimore: Williams & Wilkins.

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Research article

J. Microbiol. Biotechnol. 2023; 33(11): 1428-1436

Published online November 28, 2023 https://doi.org/10.4014/jmb.2306.06017

Copyright © The Korean Society for Microbiology and Biotechnology.

Comparative Genome analysis of the Genus Curvibacter and the Description of Curvibacter microcysteis sp. nov. and Curvibacter cyanobacteriorum sp. nov., Isolated from Fresh Water during the Cyanobacterial Bloom Period

Ve Van Le1, So-Ra Ko1, Mingyeong Kang1,2, Seonah Jeong1, Hee-Mock Oh1,2, and Chi-Yong Ahn1,2*

1Cell Factory Research Centre, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
2Department of Environmental Biotechnology, KRIBB School of Biotechnology, University of Science and Technology, Daejeon 34113, Republic of Korea

Correspondence to:Chi-Yong Ahn,       cyahn@kribb.re.kr

Received: June 8, 2023; Revised: July 27, 2023; Accepted: August 15, 2023

Abstract

The three Gram-negative, catalase- and oxidase-positive bacterial strains RS43T, HBC28, and HBC61T, were isolated from fresh water and subjected to a polyphasic study. Comparison of 16S rRNA gene sequence initially indicated that strains RS43T, HBC28, and HBC61T were closely related to species of genus Curvibacter and shared the highest sequence similarity of 98.14%, 98.21%, and 98.76%, respectively, with Curvibacter gracilis 7-1T. Phylogenetic analysis based on genome sequences placed all strains within the genus Curvibacter. The average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) values between the three strains and related type strains supported their recognition as two novel genospecies in the genus Curvibacter. Comparative genomic analysis revealed that the genus possessed an open pangenome. Based on KEGG BlastKOALA analyses, Curvibacter species have the potential to metabolize benzoate, phenylacetate, catechol, and salicylate, indicating their potential use in the elimination of these compounds from the water systems. The results of polyphasic characterization indicated that strain RS43T and HBC61T represent two novel species, for which the name Curvibacter microcysteis sp. nov. (type strain RS43T =KCTC 92793T=LMG 32714T) and Curvibacter cyanobacteriorum sp. nov. (type strain HBC61T =KCTC 92794T =LMG 32713T) are proposed.

Keywords: Curvibacter, cyanobacterial bloom, Microcystis

Introduction

The genus Curvibacter, affiliated to the family Comamonadaceae of the phylum Proteobacteria, was originally described in 2004, with Curvibacter gracilis as the type species [1]. Since then, four species with validly published names [2] have been isolated from well water [1,3] and distilled water [4]. Species of the genus Curvibacter described to date are Gram-negative, curve rod-shaped, and positive for catalase and oxidase. The members of the genus Curvibacter commonly contain C16:0, C16:1, C18:1, and C8:0 3-OH as their major fatty acids and Q-8 as their predominant respiratory quinone [1]. Currently, no comparative genome analysis has been carried out on the genus Curvibacter.

Cyanobacteria play an essential role in the carbon and nutrient cycles [5]. However, they cause harm to ecosystems and humans through the production of cyanotoxins [6]. The excessive proliferation of cyanobacteria, also known as cyanobacterial bloom, destroys biodiversity and degrades drinking water quality [6]. During the study of the role of bacterial community in the formation of cyanobacterial blooms, three new strains, RS43T, HBC28, and HBC61T, were isolated from a freshwater reservoir during the cyanobacterial bloom period. The present study aimed to determine their taxonomic status using polyphasic approach. In addition, the first comparative genomic study for the genus Curvibacter was performed to predict their ecological functions and potential biotechnological applications.

Materials and Methods

Isolation and Cultivation

Strains RS43T, HBC28, and HBC61T were isolated from Daechung Reservoir (36° 22' 33.7'' N, 127° 38' 20.6'' E) according to the procedures previously described [7]. Briefly, the sample was diluted by the standard ten-fold serial dilution method and was spread on agar plates of Reasoner’s 2A (R2A). After incubation at 25°C for 1 week under aerobic conditions, colonies were picked and purified two times by repeated subculture. The strains were then preserved in R2A medium containing 20% glycerol (v/v) at –80°C. Considering the close phylogenetic relationships, Curvibacter gracilis KCTC42831T (=7-1T), Curvibacter lanceolatus KCTC42829T (=IAM 14947T), and Curvibacter delicatus KCTC42828T (=IAM 14955T) procured from KCTC were chosen as reference strains and they were compared in the aspect of polyphasic characterization.

Molecular Identification, Genome Sequencing, and Pangenome Analysis

The whole genomic DNA was extracted using FastDNA Spin Kit for Soil (MB Biomedicals, USA). For strain identification, the 16S rRNA gene was amplified and sequenced with the universal bacterial primers of 27F, 518F, 785F, 805R, 907R, and 1492R [8-10]. Pairwise comparisons of the almost-complete 16S rRNA gene sequences of three strains and those of related taxa were performed on the latest updated EzBioCloud (www.ezbiocloud.net)[11] and NCBI blast (www.ncbi.nlm.nih.gov). The draft genomes of three strains were sequenced using the Illumina MiSeq (Macrogen Inc., South Korea) platform and annotated by Prokka v.1.12 and Rapid Annotation using Subsystems Technology (RAST). The metabolic pathways of strains RS43T, HBC28, and HBC61T were reconstructed using BlastKOALA [12]. The G+C content was calculated from the whole genome sequence. For comparative genome analysis, the genomes of Curvibacter species were obtained from NCBI (Table 1). Pangenomic analyses were performed using the EDGAR 3.0 platform [13]. The biosynthetic gene clusters of secondary metabolites were searched using AntiSMASH 7 beta [14] with strict detection.

Table 1 . General genome characteristics of RS43T, HBC28, and HBC61T and related taxa..

SpeciesStrainAccession No.Size (Mb)G+C (%)GeneProtein
Curvibacter microcysteisRS43TJAQSIN0000000004.8965.224,3824,297
Curvibacter microcysteisHBC28JAQSIO0000000004.8265.294,3994,256
Curvibacter cyanobacteriorumHBC61TJAQSIP0000000004.8567.154,2664,185
Curvibacter gracilisATCC BAA-807TJADZ000000006.7566.016,2146,036
Curvibacter lanceolatusATCC 14669TARLO000000006.8365.556,3676,157
Curvibacter delicatusNBRC 14919TBCWP000000003.7863.513,6783,543


Phylogeny

The 16S rRNA gene sequences of three strains and other closely related strains obtained from the GenBank/EMBL/DDBJ databases were aligned using the MUSCLE algorithm. To identify the phylogenetic location of three strains, phylogenetic trees were constructed by using maximum-likelihood [15], neighbor-joining [16], and minimum-evolution [17] methods with the software MEGA version 11 [18]. The confidence levels and distance matrices of phylogenetic trees were determined with 1000 bootstrap replicates and Kimura’s two-parameter model [19], respectively. To provide cogent evidence for the assignment of strains RS43T, HBC28, and HBC61T as novel species, the ANI and dDDH values were calculated using the OrthoANI algorithm and the Genome-to-Genome Distance Calculator (GGDC 2.0) [20], respectively. The two-way average amino acid identity (AAI) was calculated using AAI calculator (http://enve-omics.ce.gatech.edu/aai/) and percentage of conserved proteins (POCP) values were by using EDGAR 3.0 platform [13]. A phylogenomic tree was built utilizing the Type (Strain) Genome Server (TYGS) [21].

Phenotypic and Biochemical Properties

Morphological characteristics of strains RS43T, HBC28, and HBC61T were visualized under a CM-20 transmission electron microscope (Philips) after 3-day incubation at 25°C on R2A medium. Cell motility was identified using the hanging-drop method [22]. A Gram stain kit (Becton Dickinson, USA) was used to determine the Gram reaction. Catalase and oxidase tests were done using 3% (v/v) H2O2 and 1% (w/v) N, N, N’, N’-tetramethyl-1,4-phenylenediamine, respectively. The growth of three strains on R2A agar, Luria–Bertani agar (LBA, Difco, USA), tryptone soy agar (TSA, Difco, USA), and nutrient agar (NA, Difco, USA) was investigated at 25°C for five days. Growth tolerance ranges for temperature, pH, and NaCl were assessed by observing colony growth on R2A agar plates after 5-day incubation. The growth temperature was evaluated at 4, 10, 17, 20, 25, 30, 37, 40, and 60°C. Growth at different pH (4.0–12.0 with an interval of 1.0) was assessed by adjusting the pH using the buffer system [7]. The tolerance range for NaCl was determined by culturing strains on R2A agar plates supplemented with varying amounts of NaCl [0.0, 0.1, 0.3, 0.5, 1.0, 1.5, and 2.0% (w/v)]. Biochemical characteristics and enzyme activities were inspected using API ZYM and API 20NE kits (bioMérieux, France). Hydrolysis of Tween 20 (1.0%, w/v), Tween 80 (1.0%, w/v), and skim milk (0.5%, w/v) was tested after 3-day incubation [23].

Chemotaxonomic Characterization

For chemotaxonomic analysis, all strains were grown on R2A for 3 days at 25°C. After harvesting the cells, the fatty acids were saponified, methylated, extracted, and analyzed according to the protocol recommended by MIDI Microbial Identification System (version 6.1, MIDI) [24]. Polar lipids were extracted from lyophilized cells, separated and identified as described previously [2528]. Quinones were extracted and purified with a mixture of chloroform and methanol (2:1) for 3–4 h and analyzed by HPLC [29].

Results and Discussion

Phylogenetic Characteristics

The 16S rRNA gene sequences of strains RS43T, HBC28, and HBC61T determined by the Sanger sequencing were 1474, 1484, and 1471 bp in length, respectively. Strains RS43T, HBC28, and HBC61T were most closely related to Curvibacter gracilis 7-1T with 16S rRNA sequence similarities of 98.14%, 98.21%, and 98.76%, respectively. The 16S rRNA gene sequence of strains RS43T and HBC61T shared 99.35% similarity with each other. The phylogenetic trees revealed that the three strains formed a coherent cluster with C. gracilis 7-1T and Curvibacter lanceolatus IAM 14947T. This relationship was supported by high bootstrap percentages (Fig. 1). Therefore, the three strains were phylogenetically affiliated with the genus Curvibacter.

Figure 1. Neighbor-joining phylogenetic tree based on the 16S rRNA gene sequences depicting the phylogenetic placements of three strains among the related species. Bootstrap values above 50% are shown at branch points. Closed circles indicate that the corresponding nodes were also recovered in the maximum-likelihood and minimum-evolution methods, whereas the open circles indicate nodes recovered with neighbor-joining and maximum-likelihood algorithms.

Genomic Characteristics

The draft genome sequences of strains RS43T, HBC28, and HBC61T had a total nucleotide length of 4,895,745 bp (24 contigs), 4,822,995 bp (21 contigs), and 4,848,818 bp (19 contigs), respectively, with the sequencing depth of 148×, 147×, and 147×, respectively. Overall, the draft genome met the criteria required for the taxonomic purposes proposed [30]. The G+C contents of strains RS43T and HBC28 were estimated to be 65.22 % and 65.29 %, which correspond with the G+C content range (62.2–66.0 mol%) of members of the genus Curvibacter [1].

The genomic features of Curvibacter species are presented in Table 1. The draft genome sequences of Curvibacter species vary significantly in size, ranging from 3.78 Mbp for Curvibacter delicatus NBRC 14919T to 6.83 Mbp for Curvibacter lanceolatus ATCC 14669T. Additionally, the DNA G+C contents varied among the strains, with C. delicatus NBRC 14919T having the lowest content (63.5%) and Curvibacter cyanobacteriorum HBC61T showing the highest content (67.15%). There was a significant difference in the numbers of predicted genes among Curvibacter species, which ranged from 3678 to 6367.

Whole-Genome-Based Phylogeny

The AAI and POCP values for the three strains with the type species of the genus, C. gracilis, were found to be between 80.27-80.50% and 78.00-79.79%, respectively, which were higher than the genus boundaries of 60-80%for AAI [31] and 50% for POCP [32] (Figs. 2A-2B). These results supported that the three strains belong to the genus Curvibacter. Strains RS43T and HBC28 were found to be the same species with an ANI value of 98.13%(Fig. 2C) and a dDDH value of 83.1% (Fig. 2D). However, the ANI and dDDH values between strains RS43T and HBC61T were 86.29% and 30.7%, respectively, implying that they represent two separate Curvibacter species. The dDDH and ANI scores between the three strains and their related type strains were much lower than the recommended species cut-off level (dDDH, 70%; ANI, 95-96%), revealing their novel status within the genus Curvibacter [33,34]. The phylogenomic tree showed that the closest neighbors of the three strains were C. gracilis 7-1T and Curvibacter lanceolatus IAM 14947T (Fig. 3). Notably, Curvibacter delicatus formed a distinct clade separated from other members of the genus Curvibacter, indicating that this species may belong to other genus. Further studies are needed to identify the exact taxonomic position of this species. In summary, the whole-genome-based phylogeny clearly suggests that strains RS43T and HBC61T should be classified as two novel species within the genus Curvibacter.

Figure 2. Heat map of AAI (A), POCP (B), ANI (C), and dDDH (D) from pairwise genome comparisons. AAI, average amino acid identity; POCP, percentage of conserved proteins; ANI, average nucleotide identity; dDDH, digital DNA– DNA hybridization.
Figure 3. Phylogenomic tree inferred with FastME 2.1.6.1 from Genome BLAST Distance Phylogeny (GBDP) distances calculated from genome sequences. The branch lengths are adjusted with the GBDP distance formula d5. The GBDP pseudo-bootstrap support values from 100 replications exceeding 60% are displayed above the branches. The average support across branches is 94.6%.

Comparative Genomic Analysis

The distribution of specific genomic regions of Curvibacter species was shown in Fig. 4A. Functional analysis using the KEGG and COG database revealed that these species displayed similar distribution patterns of subsystem categories (Figs. S1-S2). For instance, most genes were involved in vital central metabolic pathways, such as “amino acid transport and metabolism”, “signal transduction mechanisms”, “transcription”, and “energy production and conversion”. In total, the “core genome” consisted of 2034 genes (Fig. 4B). 41.6% of genes were assigned to the dispensable category, whereas the percentage of singletons was estimated to be 36.9% (Fig. 4C). The lifestyle of the bacterial genus can be partly reflected by its pangenome [35]. Bacteria that inhabit a limited niche tend to have a closed pangenome, whereas bacteria living in a community generally possess an open pangenome with a high rate of horizontal gene transfer [35]. The pangenome is classified as open or closed, based on the exponent gamma value of Heaps’ law [36]. The pangenome size of Curvibacter increased while its core-genome size decreased as more genomes were added (Figs. 4D-4E). The gamma value of Heaps’ law was estimated to be 0.386, which is higher than 0, implying that Curvibacter pangenome is open (Fig. 4E) [37].

Figure 4. Comparative genomic analysis. Circular view of the genome of Curvibacter species (A). The number (B) and percentage (C) of common core genes across all Curvibacter species. Core genome (D) and pangenome (E) profiles of Curvibacter species. The fitted exponential Heaps’ law function is represented by the red curve while the upper and lower boundaries of the 95% confidence internal are indicated by the green and blue curves, respectively.

The core gene proportion of all strains of Curvibacter species was more enriched with COG functions involved in “RNA processing and modification”, “chromatin structure and dynamics”, and “translation”. In contrast, most singleton genes were related to “transposase”, “defense mechanisms”, and “intracellular trafficking” (Fig. 5A). To understand the ecological function of Curvibacter species, their potential for vitamin synthesis and biosynthesis of secondary metabolites was predicted. Bacteria produce several secondary metabolites to communicate with other microorganisms [38]. Strains RS43T, HBC28, and HBC61T possessed putative secondary metabolite gene clusters potentially related to the synthesis of terpene and beta-lactone (Fig. 5B). Terpene, which was also predicted in all Curvibacter species, plays an essential role in the defense mechanisms of plants and fungi [39]. Beta-lactones have been reported to show antimicrobial activities and can be used as building blocks for complex compounds such as antibiotics and anticancer drugs [40]. Among Curvibacter species, C. gracilis ATCCBAA-807T harbored the highest secondary metabolite biosynthetic gene clusters. This strain can produce terpene, beta-lactone, Type 1 polyketide synthase (T1PKS), and nonribosomal peptide synthetase (NRPS). As NRPS was predicted in the genome of C. gracilis ATCCBAA-807T, this strain may produce antimicrobial, antiviral, anticancer, and anti-inflammatory compounds [41]. Bacteria can support algal growth by supplying vitamin B and iron [42]. Curvibacter species can promote the growth of the cyanobacterium Microcystis [43]. Given that Curvibacter species possess the biosynthetic pathway for cobalamin (vitamin B12) and biotin (vitamin B7) in their genome (Fig. 5C), they have the potential to provide these vitamins to cyanobacteria, thereby facilitating the formation of cyanobacterial blooms.

Figure 5. Functional genome analysis of Curvibacter species. The distribution of core, dispensable, and singletons (A). Gene clusters predicted in the genomes of Curvibacter species involved in secondary metabolite synthesis (B), Metabolism of cofactors and vitamins and xenobiotics biodegradation in the genomes of Curvibacter species (C).

Aromatic compounds, which constitute approximately 25% of the world's biomass, are the second most prevalent group of organic compounds in nature after carbohydrates [44]. They are considered one of the most persistent pollutants in the environment [45]. The metabolic capacities of Curvibacter species predicted using BlastKOALA suggested that they could metabolize the xenobiotic substances, such as benzoate (C. gracilis ATCC BAA-807T and C. lanceolatus ATCC 14669T), phenylacetate (C. gracilis ATCC BAA-807T), catechol (all strains except for C. delicatus NBRC 14919T), and salicylate (RS43T and HBC28) (Fig. 5C). Therefore, they have the potential to remove these compounds from water systems.

Phenotypic Characteristics

The cells of strains RS43T, HBC28, and HBC61T were observed to be Gram-negative, rod-shaped with flagella (Fig. S3), and catalase- and oxidase-positive. The colonies appeared circular, smooth, convex, and colorless with a diameter of 1–2 mm after 3 days of growth on R2A agar medium at 25°C. These strains grew well on R2A and NA media but not on LBA and TSA media. They were positive for hydrolysis of Tween 80, but negative for hydrolysis of Tween 20 and skim milk. Growth occurred within the pH range of 5.5 to 10. Several phenotypic features distinguish strain RS43T and strain HBC61T, confirming they belong to two different species. For instance, strain HBC61T assimilated D-mannitol and gluconate, exhibited growth at 40°C, and was able to tolerate NaCl concentration up to 1% (w/v), whereas strain RS43T did not. Table 2 provides further details on the additional phenotypic features distinguishing strains RS43T, HBC28, and HBC61T from their closely related strains.

Table 2 . Differential phenotypic characteristics of strains RS43T, HBC28, and HBC61T and their phylogenetic neighbors..

Characteristic123456
Hydrolysis of Tween 20---+--
Optimal growth range
pH7.5-8.57.5-8.56.0-8.05.0-8.0aneutrophilicb5.5-8.5c
Temperature (°C)20-3020-3020-3725-30a20-30b30-32c
Biochemical characteristics (API ZYM, API 20NE)
Esterase (C4)+++++-
Esterase lipase (C8)+++++-
Cystine arylamidase---++-
Reduction of nitrates to nitrites---+++
Urea hydrolysis-+++++
Assimilation of
D-Glucose---+--
D-Mannitol--+---
Gluconate--++--

Taxa: 1, strain RS43T; 2, HBC28; 3, HBC61T; 4, Curvibacter gracilis KCTC42831T; 5, Curvibacter lanceolatus KCTC42829T; 6, Curvibacter delicatus KCTC 42828T. +, positive; −, negative. aData were obtained from [3]; bData were obtained from [4]; cData were obtained from [46]..



Chemotaxonomic Characteristics

The fatty acid profile of strains RS43T, HBC28, and HBC61T showed a similar pattern to those of the reference strains (Table 3). All strains had major fatty acids (> 10% of total fatty acids) that included summed feature 3 (C16:1ω7c and/or C16:1ω6c), summed feature 8 (C18:1 ω7c and/or C18:1 ω6c), and C16:0. Strains RS43T, HBC28, and HBC61T possessed Q-8 as the major quinone, which is consistent with the ubiquinone feature of the genus Curvibacter. The major polar lipid profile identified in strains RS43T and HBC61T consisted of phosphatidyl-ethanolamine, diphosphatidylglycerol, and unidentified lipids (Fig. S4). However, strain HBC61T could be distinguished from strain RS43T by the presence of an additional unidentified phospholipid as a major component.

Table 3 . Fatty acid compositions (%) of strains RS43T, HBC28, and HBC61T and their phylogenetic neighbors..

Fatty Acids123456
C8:0 3-OH4.44.23.73.7ND4.2
C12:04.43.73.63.33.7ND
C14:0NDNDNDNDTRND
C16:014.315.916.220.820.133.2
C17:1 ω6cNDNDND1.44TRND
C17:0 cycloNDNDNDNDND5.8
C18:1 ω9cNDNDTRTRND1.1
C18:1 ω7c 11-methyl1.03TRTRNDTRTR
Summed Feature 3*42.843.343.142.643.139.0
Summed Feature 8*32.631.630.426.329.515.7

Taxa: 1, strain RS43T; 2, HBC28; 3, HBC61T; 4, Curvibacter gracilis KCTC42831T; 5, Curvibacter lanceolatus KCTC42829T; 6, Curvibacter delicatus KCTC 42828T. Major fatty acids (> 10.0%) are highlighted as bold type. TR, trace amount (< 1%); ND, not detected. *Summed features refer to fatty acids that cannot be distinctly differentiated from another fatty acid and these fatty acids are grouped as one feature with a single percentage of the total. Summed feature 3 contained C16:1 ω6c and/or C16:1 ω7c. Summed feature 8 contained C18:1 ω7c and/or C18:1 ω6c..



Description of Curvibacter microcysteis sp. nov.

Curvibacter microcysteis sp. nov. (mi.cro.cys'te.is N.L. gen. n. microcysteis of the cyanobacterial genus Microcystis). Cells are rod-shaped, 1.2–2.8 μm in length and 0.7–1.0 μm in width. Colonies grown on R2A agar are smooth, convex, and colorless with a 1–2 mm diameter. Motile with peritrichous flagella. Growth was observed at the temperature range of 10–37°C, up to 0.5% NaCl, and pH 5.5–10. Catalase and oxidase are positive. Able to hydrolyze Tween 80. Positive for esterase (C4), esterase lipase (C8), leucine arylamidase, acid phosphatase, and naphthol-AS-BI-phosphohydrolase. The major fatty acids were summed feature 3 (C16:1 ω7c and/or C16:1 ω6c), summed feature 8 (C18:1 ω7c and/or C18:1 ω6c), and C16:0. The quinone was Q-8. The major polar lipids were phosphatidylethanolamine, diphosphatidylglycerol, and two unidentified lipids.

The type strain RS43T (=KCTC 92793T = LMG 32714T) was isolated from fresh water. The 16S rRNA gene sequence and the genomic sequence of strain RS43T have been deposited under the GenBank/EMBL/DDBJ accession numbers OQ642155 and JAQSIN000000000, respectively.

Description of Curvibacter cyanobacteriorum sp. nov.

Curvibacter cyanobacteriorum sp. nov. (cy.a.no.bac.te.ri.órum. N.L. gen. pl. n. cyanobacteriorum of cyanobacteria).

Cells are rod-shaped, 1.2–2.7 μm in length and 0.7–0.9 μm in width. Colonies grown on R2A agar are smooth, convex, and colorless with a 1–2 mm diameter. Motile with monotrichous flagellum. Growth was observed at the temperature range of 10–40°C, up to 1% NaCl, and pH 5.5–10. Catalase and oxidase are positive. Able to hydrolyze Tween 80. Positive for esterase (C4), esterase lipase (C8), leucine arylamidase, acid phosphatase, and naphthol-AS-BI-phosphohydrolase, hydrolysis of urea, and assimilation of D-mannitol and potassium gluconate. The major fatty acids were summed feature 3 (C16:1 ω7c and/or C16:1 ω6c), summed feature 8 (C18:1 ω7c and/or C18:1 ω6c), and C16:0. The quinone was Q-8. The major polar lipids were phosphatidylethanolamine, diphosphatidylglycerol, one unidentified phospholipid, and two unidentified lipids.

The type strain HBC61T (=KCTC 92794T = LMG 32713T) was isolated from fresh water. The 16S rRNA gene sequence and the genomic sequence of strain HBC61T have been deposited under the GenBank/EMBL/DDBJ accession numbers OQ642154 and JAQSIP000000000, respectively.

Conclusions

Considering chemotaxonomic, phylogenetic, and phenotypic characteristics, strains RS43T, HBC28, and HBC61T belonged to the genus Curvibacter. Genome-relatedness indices, phenotypic and chemotaxonomic characteristics precisely differentiated them from all known Curvibacter species. Along with phylogenetic distinctiveness, strain HBC61T was distinguished from RS43T and HBC28 by several phenotypic and chemotypic features. Therefore, strains RS43T, HBC28, and HBC61T should be classified as two novel species of the genus Curvibacter, for which the names Curvibacter microcysteis sp. nov. (RS43T = KCTC 92793T = LMG 32714T) and Curvibacter cyanobacteriorum sp. nov. (HBC61T = KCTC 92794T = LMG 32713T).

Supplemental Materials

Acknowledgments

This research was supported by Korea Environment Industry & Technology Institute (KEITI) through Aquatic Ecosystem Conservation Research Program (2022003050004) and the National Research Foundation of Korea (2023R1A2C1003308) and the Korea Research Institute of Bioscience and Biotechnology (KRIBB) Research Initiative Program (KGM5252322).

Conflict of Interest

The authors have no financial conflicts of interest to declare.

Fig 1.

Figure 1.Neighbor-joining phylogenetic tree based on the 16S rRNA gene sequences depicting the phylogenetic placements of three strains among the related species. Bootstrap values above 50% are shown at branch points. Closed circles indicate that the corresponding nodes were also recovered in the maximum-likelihood and minimum-evolution methods, whereas the open circles indicate nodes recovered with neighbor-joining and maximum-likelihood algorithms.
Journal of Microbiology and Biotechnology 2023; 33: 1428-1436https://doi.org/10.4014/jmb.2306.06017

Fig 2.

Figure 2.Heat map of AAI (A), POCP (B), ANI (C), and dDDH (D) from pairwise genome comparisons. AAI, average amino acid identity; POCP, percentage of conserved proteins; ANI, average nucleotide identity; dDDH, digital DNA– DNA hybridization.
Journal of Microbiology and Biotechnology 2023; 33: 1428-1436https://doi.org/10.4014/jmb.2306.06017

Fig 3.

Figure 3.Phylogenomic tree inferred with FastME 2.1.6.1 from Genome BLAST Distance Phylogeny (GBDP) distances calculated from genome sequences. The branch lengths are adjusted with the GBDP distance formula d5. The GBDP pseudo-bootstrap support values from 100 replications exceeding 60% are displayed above the branches. The average support across branches is 94.6%.
Journal of Microbiology and Biotechnology 2023; 33: 1428-1436https://doi.org/10.4014/jmb.2306.06017

Fig 4.

Figure 4.Comparative genomic analysis. Circular view of the genome of Curvibacter species (A). The number (B) and percentage (C) of common core genes across all Curvibacter species. Core genome (D) and pangenome (E) profiles of Curvibacter species. The fitted exponential Heaps’ law function is represented by the red curve while the upper and lower boundaries of the 95% confidence internal are indicated by the green and blue curves, respectively.
Journal of Microbiology and Biotechnology 2023; 33: 1428-1436https://doi.org/10.4014/jmb.2306.06017

Fig 5.

Figure 5.Functional genome analysis of Curvibacter species. The distribution of core, dispensable, and singletons (A). Gene clusters predicted in the genomes of Curvibacter species involved in secondary metabolite synthesis (B), Metabolism of cofactors and vitamins and xenobiotics biodegradation in the genomes of Curvibacter species (C).
Journal of Microbiology and Biotechnology 2023; 33: 1428-1436https://doi.org/10.4014/jmb.2306.06017

Table 1 . General genome characteristics of RS43T, HBC28, and HBC61T and related taxa..

SpeciesStrainAccession No.Size (Mb)G+C (%)GeneProtein
Curvibacter microcysteisRS43TJAQSIN0000000004.8965.224,3824,297
Curvibacter microcysteisHBC28JAQSIO0000000004.8265.294,3994,256
Curvibacter cyanobacteriorumHBC61TJAQSIP0000000004.8567.154,2664,185
Curvibacter gracilisATCC BAA-807TJADZ000000006.7566.016,2146,036
Curvibacter lanceolatusATCC 14669TARLO000000006.8365.556,3676,157
Curvibacter delicatusNBRC 14919TBCWP000000003.7863.513,6783,543

Table 2 . Differential phenotypic characteristics of strains RS43T, HBC28, and HBC61T and their phylogenetic neighbors..

Characteristic123456
Hydrolysis of Tween 20---+--
Optimal growth range
pH7.5-8.57.5-8.56.0-8.05.0-8.0aneutrophilicb5.5-8.5c
Temperature (°C)20-3020-3020-3725-30a20-30b30-32c
Biochemical characteristics (API ZYM, API 20NE)
Esterase (C4)+++++-
Esterase lipase (C8)+++++-
Cystine arylamidase---++-
Reduction of nitrates to nitrites---+++
Urea hydrolysis-+++++
Assimilation of
D-Glucose---+--
D-Mannitol--+---
Gluconate--++--

Taxa: 1, strain RS43T; 2, HBC28; 3, HBC61T; 4, Curvibacter gracilis KCTC42831T; 5, Curvibacter lanceolatus KCTC42829T; 6, Curvibacter delicatus KCTC 42828T. +, positive; −, negative. aData were obtained from [3]; bData were obtained from [4]; cData were obtained from [46]..


Table 3 . Fatty acid compositions (%) of strains RS43T, HBC28, and HBC61T and their phylogenetic neighbors..

Fatty Acids123456
C8:0 3-OH4.44.23.73.7ND4.2
C12:04.43.73.63.33.7ND
C14:0NDNDNDNDTRND
C16:014.315.916.220.820.133.2
C17:1 ω6cNDNDND1.44TRND
C17:0 cycloNDNDNDNDND5.8
C18:1 ω9cNDNDTRTRND1.1
C18:1 ω7c 11-methyl1.03TRTRNDTRTR
Summed Feature 3*42.843.343.142.643.139.0
Summed Feature 8*32.631.630.426.329.515.7

Taxa: 1, strain RS43T; 2, HBC28; 3, HBC61T; 4, Curvibacter gracilis KCTC42831T; 5, Curvibacter lanceolatus KCTC42829T; 6, Curvibacter delicatus KCTC 42828T. Major fatty acids (> 10.0%) are highlighted as bold type. TR, trace amount (< 1%); ND, not detected. *Summed features refer to fatty acids that cannot be distinctly differentiated from another fatty acid and these fatty acids are grouped as one feature with a single percentage of the total. Summed feature 3 contained C16:1 ω6c and/or C16:1 ω7c. Summed feature 8 contained C18:1 ω7c and/or C18:1 ω6c..


References

  1. Ding L, Yokota A. 2004. Proposals of Curvibacter gracilis gen. nov., sp. nov. and Herbaspirillum putei sp. nov. for bacterial strains isolated from well water and reclassification of [Pseudomonas] huttiensis, [Pseudomonas] lanceolata, [Aquaspirillum] delicatum and [Aquaspirillum] autotrophicum as Herbaspirillum huttiense comb. nov., Curvibacter lanceolatus comb. nov., Curvibacter delicatus comb. nov. and Herbaspirillum autotrophicum comb. nov. . Int. J. Syst. Evol. Microbiol. 54: 2223-2230.
    Pubmed CrossRef
  2. Parte AC, Carbasse JS, Meier-Kolthoff JP, Reimer LC, Göker M. 2020. List of prokaryotic names with standing in nomenclature (LPSN) moves to the DSMZ. Int. J. Syst. Evol. Microbiol. 70: 5607-5612.
    Pubmed KoreaMed CrossRef
  3. Ding L, Yokota A. 2010. Curvibacter fontana sp. nov., a microaerobic bacteria isolated from well water. J. Gen. Appl. Microbiol. 56: 267-271.
    Pubmed CrossRef
  4. Leifson E. 1962. The bacterial flora of distilled and stored water. III. New species of the genera Corynebacterium, Flavobacterium, Spirillum and Pseudomonas. Int. Bull. Bacteriol. Nomencl. Taxon. 12: 161-170.
    CrossRef
  5. Bullerjahn GS, Post AF. 2014. Physiology and molecular biology of aquatic cyanobacteria. Front. Microbiol. 5: 359.
    Pubmed KoreaMed CrossRef
  6. Huisman J, Codd GA, Paerl HW, Ibelings BW, Verspagen JMH, Visser PM. 2018. Cyanobacterial blooms. Nat. Rev. Microbiol. 16: 471-483.
    Pubmed CrossRef
  7. Le VV, Ko SR, Kang M, Lee SA, Oh HM, Ahn CY. 2022. Panacibacter microcysteis sp. nov., isolated from a eutrophic reservoir during the Microcystis bloom period. Arch. Microbiol. 204: 291.
    Pubmed CrossRef
  8. Weisburg WG, Barns SM, Pelletier DA, Lane DJ. 1991. 16S ribosomal DNA amplification for phylogenetic study. J. Bacteriol. 173: 697-703.
    Pubmed KoreaMed CrossRef
  9. Baker GC, Smith JJ, Cowan DA. 2003. Review and re-analysis of domain-specific 16S primers. J. Microbiol. Methods 55: 541-555.
    Pubmed CrossRef
  10. Youssef N, Sheik CS, Krumholz LR, Najar FZ, Roe BA, Elshahed MS. 2009. Comparison of species richness estimates obtained using nearly complete fragments and simulated pyrosequencing-generated fragments in 16S rRNA gene-based environmental surveys. Appl. Environ. Microbiol. 75: 5227-5236.
    Pubmed KoreaMed CrossRef
  11. Yoon SH, Ha SM, Kwon S, Lim J, Kim Y, Seo H, et al. 2017. Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies. Int. J. Syst. Evol. Microbiol. 67: 1613-1617.
    Pubmed KoreaMed CrossRef
  12. Kanehisa M, Sato Y, Morishima K. 2016. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J. Mol. Biol. 428: 726-731.
    Pubmed CrossRef
  13. Dieckmann MA, Beyvers S, Nkouamedjo-Fankep RC, Hanel PHG, Jelonek L, Blom J, et al. 2021. EDGAR3.0: comparative genomics and phylogenomics on a scalable infrastructure. Nucleic Acids Res. 49: W185-W192.
    Pubmed KoreaMed CrossRef
  14. Blin K, Shaw S, Steinke K, Villebro R, Ziemert N, Lee SY, et al. 2019. AntiSMASH 5.0: updates to the secondary metabolite genome mining pipeline. Nucleic Acids Res. 47: W81-W87.
    Pubmed KoreaMed CrossRef
  15. Felsenstein J. 1981. Evolutionary trees from DNA sequences: a maximum likelihood approach. J. Mol. Evol. 17: 368-376.
    Pubmed CrossRef
  16. Saitou N, Nei M. 1987. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4: 406-425.
  17. Nei M, Kumar S, Takahashi K. 1998. The optimization principle in phylogenetic analysis tends to give incorrect topologies when the number of nucleotides or amino acids used is small. Proc. Natl. Acad. Sci. USA 95: 12390-12397.
    Pubmed KoreaMed CrossRef
  18. Tamura K, Stecher G, Kumar S. 2021. MEGA11: molecular evolutionary genetics analysis version 11. Mol. Biol. Evol. 38: 3022-3027.
    Pubmed KoreaMed CrossRef
  19. Kimura M. 1983. The Neutral Theory of Molecular Evolution. Cambride: Cambridge University Press.
  20. Meier-Kolthoff JP, Auch AF, Klenk HP, Göker M. 2013. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinformatics 14: 60.
    Pubmed KoreaMed CrossRef
  21. Meier-Kolthoff JP, Göker M. 2019. TYGS is an automated high-throughput platform for state-of-the-art genome-based taxonomy. Nat. Commun. 10: 2182.
    Pubmed KoreaMed CrossRef
  22. Skerman VBD. 1967. A Guide to the Identification of the Genera of Bacteria. 2nd edition. The Williams & Wilkins Co.
  23. Smibert RM, Krieg NR. 1994. Phenotypic characterization, pp 607-654, In Gerhardt P, Murray RGE, Wood WA, Krieg NR (eds.), Methods for General and Molecular Bacteriology. American Society for Microbiology, Washington.
  24. Sasser M. 1990. Identification of Bacteria by Gas Chromatography of Cellular Fatty Acids, MIDI Technical Note 101. Newark, DE: MIDI Inc.
  25. Tindall BJ, Sikorski J, Smibert RA, Krieg NR. 2007. Phenotypic characterization and the principles of comparative systematic, pp. 330-393. In Reddy CA, Beveridge TJ, Breznak JA, Marzluf GA, Schmidt TM, Snyder LR (eds.), Methods for General and Molecular Bacteriology. Washington, DC: American Society for Microbiology.
  26. Minnikin DE, O'Donnell AG, Goodfellow M, Alderson G, Athalye M, Schaal A, et al. 1984. An integrated procedure for the extraction of bacterial isoprenoid quinones and polar lipids. J. Microbiol. Methods 2: 233-241.
    CrossRef
  27. Oren A, Duker S, Ritter S. 1996. The polar lipid composition of Walsby's square bacterium. FEMS Microbiol. Lett. 138: 135-140.
    CrossRef
  28. Kates M. 1972. Techniques of Lipidology: Isolation, Analysis and Identification of Lipids. Amsterdam: North-Holland Pub. Co.
  29. Tamaoka J. 1986. Analysis of bacterial menaquinone mixtures by reverse-phase high-performance liquid chromatography. Methods Enzymol. 123: 251-256.
    Pubmed CrossRef
  30. Chun J, Oren A, Ventosa A, Christensen H, Arahal DR, da Costa MS, et al. 2018. Proposed minimal standards for the use of genome data for the taxonomy of prokaryotes. Int. J. Syst. Evol. Microbiol. 68: 461-466.
    Pubmed CrossRef
  31. Luo C, Rodriguez-R LM, Konstantinidis KT. 2014. MyTaxa: an advanced taxonomic classifier for genomic and metagenomic sequences. Nucleic Acids Res. 42: e73.
    Pubmed KoreaMed CrossRef
  32. Qin QL, Xie B Bin, Zhang XY, Chen XL, Zhou BC, Zhou J, et al. 2014. A proposed genus boundary for the prokaryotes based on genomic insights. J. Bacteriol. 196: 2210-2215.
    Pubmed KoreaMed CrossRef
  33. Richter M, Rosselló-Móra R. 2009. Shifting the genomic gold standard for the prokaryotic species definition. Proc. Natl. Acad. Sci. USA 106: 19126-19131.
    Pubmed KoreaMed CrossRef
  34. Auch AF, von Jan M, Klenk HP, Göker M. 2010. Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison. Stand. Genomic Sci. 2: 117-134.
    Pubmed KoreaMed CrossRef
  35. Rouli L, Merhej V, Fournier PE, Raoult D. 2015. The bacterial pangenome as a new tool for analysing pathogenic bacteria. New Microbes New Infect. 7: 72-85.
    Pubmed KoreaMed CrossRef
  36. Park SC, Lee K, Kim YO, Won S, Chun J. 2019. Large-scale genomics reveals the genetic characteristics of seven species and importance of phylogenetic distance for estimating pan-genome size. Front. Microbiol. 10: 834.
    Pubmed KoreaMed CrossRef
  37. Tettelin H, Riley D, Cattuto C, Medini D. 2008. Comparative genomics: the bacterial pan-genome. Curr. Opin. Microbiol. 11: 472-477.
    Pubmed CrossRef
  38. Osbourn A. 2010. Secondary metabolic gene clusters: evolutionary toolkits for chemical innovation. Trends Genet. 26: 449-457.
    Pubmed CrossRef
  39. Oldfield E, Lin FY. 2012. Terpene biosynthesis: modularity rules. Angew. Chem. - Int. Ed. 51: 1124-1137.
    Pubmed KoreaMed CrossRef
  40. Robinson SL, Christenson JK, Wackett LP. 2019. Biosynthesis and chemical diversity of β-lactone natural products. Nat. Prod. Rep. 36: 458-475.
    Pubmed CrossRef
  41. Agrawal S, Acharya D, Adholeya A, Barrow CJ, Deshmukh SK. 2017. Nonribosomal peptides from marine microbes and their antimicrobial and anticancer potential. Front. Pharmacol. 8: 828.
    Pubmed KoreaMed CrossRef
  42. Croft MT, Lawrence AD, Raux-Deery E, Warren MJ, Smith AG. 2005. Algae acquire vitamin B12 through a symbiotic relationship with bacteria. Nature 438: 90-93.
    Pubmed CrossRef
  43. Kim M, Lee J, Yang D, Park HY, Park W. 2020. Seasonal dynamics of the bacterial communities associated with cyanobacterial blooms in the Han River. Environ. Pollut. 266: 115198.
    Pubmed CrossRef
  44. Valderrama JA, Durante-Rodríguez G, Blázquez B, García JL, Carmona M, Díaz E. 2012. Bacterial degradation of benzoate: crossregulation between aerobic and anaerobic pathways. J. Biol. Chem. 287: 10494-10508.
    Pubmed KoreaMed CrossRef
  45. Seo J-S, Keum Y-S, Li Q. 2009. Bacterial degradation of aromatic compounds. Int. J. Environ. Res. Public Health 6: 278-309.
    Pubmed KoreaMed CrossRef
  46. Krieg NR. 1984. Genus Aquaspirillum. Hylemon, Wells, Krieg and Jannasch 1973, 361AL, In Krieg NR, Holt JG (eds.), Bergey’s Manual of Systematic Bacteriology. Baltimore: Williams & Wilkins.