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Abstract

Three aerobic, pink-pigmented, Gram-negative, motile and rod-shaped bacterial strains, designated SD21, SI9 and SB2, were isolated from the phyllosphere of healthy litchis collected from three main producing sites of Guangdong Province, PR China. The 16S rRNA gene analysis showed that strains SD21 and SI9 belonged to the genus (.) with the highest similarity to DSM 19563 (98.7%) and CBMB27 (99.8%), respectively, while strain SB2 belonged to the genus (.) and showed the highest similarity to DSM 14458 (98.6%). Phylogenomic analysis based on 92 core genes clearly showed that the most closely related type strains of SD21, SI9 and SB2 were DSM 19563, ICMP 17619 and CGMCC 1.6474, respectively. The ANI and dDDH values between the three isolates and their most closely related type strains were 85.6‒90.1% and 29.5‒40.4%, respectively, much below the threshold values for species delimitation. The isolates showed clear differences from their closely related type strains in terms of growth conditions, enzyme activities, substrates assimilation and contents of the major fatty acids. They all took summed feature 8 (C ω7c and/or C ω6c) as the major fatty acid, ubiquinone 10 as the predominant respiratory quinone and phosphatidylglycerol, diphosphatidylglycerol, phosphatidylethanolamine and phosphatidylcholine as the major polar lipids. The phenotypic, phylogenetic and chemotaxonomic analyses with genome comparison strongly support that the isolates represent three distinct novel species within the genera of and , for which the names sp. nov., sp. nov. and sp. nov. are proposed, with SD21 (=GDMCC 1.4327=KCTC 8300), SI9 (=GDMCC 1.4329=KCTC 8298) and SB2 (=GDMCC 1.4328=KCTC 8299) as the type strains, respectively.

Funding
This study was supported by the:
  • Special Fund Project for Science and Technology Innovation Strategy of Guangdong Province (Award 2019QN01N107)
    • Principle Award Recipient: XinqiangXie
  • the Guangdong Strategic Special Fund for Rural Revitalization (Award 2023-WBH-00-001)
    • Principle Award Recipient: HonghuiZhu
  • the GDAS’ Project of Science and Technology Development (Award 2022GDASZH-2022010201)
    • Principle Award Recipient: HonghuiZhu
  • the Guangdong Special Support Program (Award 2021JC06N628)
    • Principle Award Recipient: HonghuiZhu
  • the Science and Technology Program of Guangdong Province (Award 2021B1212050022)
    • Principle Award Recipient: HonghuiZhu
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2025-01-09
2025-01-25
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References

  1. Patt TE, Cole GC, Hanson RS. Methylobacterium, a new genus of facultatively methylotrophic bacteria. Int J Syst Evol Microbiol 1976; 26:226–229 [View Article]
    [Google Scholar]
  2. Leducq J-B, Sneddon D, Santos M, Condrain-Morel D, Bourret G et al. Comprehensive phylogenomics of Methylobacterium reveals four evolutionary distinct groups and underappreciated phyllosphere diversity. Genome Biol Evol 2022; 14:evac123 [View Article] [PubMed]
    [Google Scholar]
  3. Knief C, Ramette A, Frances L, Alonso-Blanco C, Vorholt JA. Site and plant species are important determinants of the Methylobacterium community composition in the plant phyllosphere. ISME J 2010; 4:719–728 [View Article] [PubMed]
    [Google Scholar]
  4. Vorholt JA. Microbial life in the phyllosphere. Nat Rev Microbiol 2012; 10:828–840 [View Article] [PubMed]
    [Google Scholar]
  5. Galbally IE, Kirstine W. The production of methanol by flowering plants and the global cycle of methanol. J Atmos Chem 2002; 43:195–229 [View Article]
    [Google Scholar]
  6. Jourand P, Giraud E, Béna G, Sy A, Willems A et al. Methylobacterium nodulans sp. nov., for a group of aerobic, facultatively methylotrophic, legume root-nodule-forming and nitrogen-fixing bacteria. Int J Syst Evol Microbiol 2004; 54:2269–2273 [View Article] [PubMed]
    [Google Scholar]
  7. Sy A, Giraud E, Jourand P, Garcia N, Willems A et al. Methylotrophic Methylobacterium bacteria nodulate and fix nitrogen in symbiosis with legumes. J Bacteriol 2001; 183:214–220 [View Article] [PubMed]
    [Google Scholar]
  8. Palberg D, Kisiała A, Jorge GL, Emery RJN. A survey of Methylobacterium species and strains reveals widespread production and varying profiles of cytokinin phytohormones. BMC Microbiol 2022; 22:49 [View Article] [PubMed]
    [Google Scholar]
  9. Krug L, Morauf C, Donat C, Müller H, Cernava T et al. Plant growth-promoting methylobacteria selectively increase the biomass of biotechnologically relevant microalgae. Front Microbiol 2020; 11:427 [View Article] [PubMed]
    [Google Scholar]
  10. Green PN, Ardley JK. Review of the genus Methylobacterium and closely related organisms: a proposal that some Methylobacterium species be reclassified into a new genus, Methylorubrum gen. nov. Int J Syst Evol Microbiol 2018; 68:2727–2748 [View Article] [PubMed]
    [Google Scholar]
  11. Parte AC, Sardà Carbasse J, Meier-Kolthoff JP, Reimer LC, Göker M. List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ. Int J Syst Evol Microbiol 2020; 70:5607–5612 [View Article] [PubMed]
    [Google Scholar]
  12. Dalton H, Whittenbury R. The acetylene reduction technique as an assay for nitrogenase activity in the methane oxidizing bacterium Methylococcus capsulatus strain bath. Arch Microbiol 1976; 109:147–151 [View Article]
    [Google Scholar]
  13. Weisburg WG, Barns SM, Pelletier DA, Lane DJ. 16S ribosomal DNA amplification for phylogenetic study. J Bacteriol 1991; 173:697–703 [View Article] [PubMed]
    [Google Scholar]
  14. Yoon S-H, Ha S-M, Kwon S, Lim J, Kim Y et al. Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies. Int J Syst Evol Microbiol 2017; 67:1613–1617 [View Article] [PubMed]
    [Google Scholar]
  15. Saitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 1987; 4:406–425 [View Article] [PubMed]
    [Google Scholar]
  16. Fitch WM. Toward defining the course of evolution: minimum change for a specific tree topology. Syst Zool 1971; 20:406 [View Article]
    [Google Scholar]
  17. Felsenstein J. Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol 1981; 17:368–376 [View Article] [PubMed]
    [Google Scholar]
  18. Tamura K, Stecher G, Kumar S. MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Mol Biol Evol 2021; 38:3022–3027 [View Article] [PubMed]
    [Google Scholar]
  19. Tamura K. Estimation of the number of nucleotide substitutions when there are strong transition-transversion and G+C-content biases. Mol Biol Evol 1992; 9:678–687 [View Article] [PubMed]
    [Google Scholar]
  20. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 2012; 19:455–477 [View Article] [PubMed]
    [Google Scholar]
  21. Nordberg H, Cantor M, Dusheyko S, Hua S, Poliakov A et al. The genome portal of the Department of Energy Joint Genome Institute: 2014 updates. Nucleic Acids Res 2014; 42:D26–31 [View Article] [PubMed]
    [Google Scholar]
  22. Lee I, Chalita M, Ha S-M, Na S-I, Yoon S-H et al. ContEst16S: an algorithm that identifies contaminated prokaryotic genomes using 16S RNA gene sequences. Int J Syst Evol Microbiol 2017; 67:2053–2057 [View Article] [PubMed]
    [Google Scholar]
  23. Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res 2015; 25:1043–1055 [View Article] [PubMed]
    [Google Scholar]
  24. Na S-I, Kim YO, Yoon S-H, Ha S, Baek I et al. UBCG: up-to-date bacterial core gene set and pipeline for phylogenomic tree reconstruction. J Microbiol 2018; 56:280–285 [View Article]
    [Google Scholar]
  25. Yoon SH, Ha SM, Lim J, Kwon S, Chun J. A large-scale evaluation of algorithms to calculate average nucleotide identity. Antonie van Leeuwenhoek 2017; 110:1281–1286 [View Article] [PubMed]
    [Google Scholar]
  26. Meier-Kolthoff JP, Auch AF, Klenk HP, Göker M. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinform 2013; 14:60 [View Article] [PubMed]
    [Google Scholar]
  27. Aziz RK, Bartels D, Best AA, DeJongh M, Disz T et al. The RAST Server: rapid annotations using subsystems technology. BMC Genom 2008; 9:75 [View Article] [PubMed]
    [Google Scholar]
  28. Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res 2014; 42:D206–D214 [View Article] [PubMed]
    [Google Scholar]
  29. Alcántara-Martínez N, Figueroa-Martínez F, Rivera-Cabrera F, Gutiérrez-Sánchez G, Volke-Sepúlveda T. An endophytic strain of Methylobacterium sp. increases arsenate tolerance in Acacia farnesiana (L.) willd: a proteomic approach. Sci Total Environ 2018; 625:762–774 [View Article] [PubMed]
    [Google Scholar]
  30. Kwak M-J, Jeong H, Madhaiyan M, Lee Y, Sa T-M et al. Genome information of Methylobacterium oryzae, a plant-probiotic methylotroph in the phyllosphere. PLoS One 2014; 9:e106704 [View Article] [PubMed]
    [Google Scholar]
  31. Richter M, Rosselló-Móra R. Shifting the genomic gold standard for the prokaryotic species definition. Proc Natl Acad Sci U S A 2009; 106:19126–19131 [View Article] [PubMed]
    [Google Scholar]
  32. Buck JD. Nonstaining (KOH) method for determination of gram reactions of marine bacteria. Appl Environ Microbiol 1982; 44:992–993 [View Article] [PubMed]
    [Google Scholar]
  33. McDonald IR, Murrell JC. The methanol dehydrogenase structural gene mxaF and its use as a functional gene probe for methanotrophs and methylotrophs. Appl Environ Microbiol 1997; 63:3218–3224 [View Article] [PubMed]
    [Google Scholar]
  34. Atlas RM. Handbook of Microbiological Media, 4th edn Washington, DC: Taylor & Francis Group; 2010 p 95
    [Google Scholar]
  35. Tindall BJ, Sikorski J, Smibert RA, Krieg NR. Phenotypic characterization and the principles of comparative systematics. In Reddy CA, Beveridge TJ, Breznak JA, Marzluf GA, Schmidt TM et al. eds Methods for General and Molecular Microbiology, 3rd edn. Washington, DC: ASM Press; 2007 pp 330–393 [View Article]
    [Google Scholar]
  36. Pérez-Miranda S, Cabirol N, George-Téllez R, Zamudio-Rivera LS, Fernández FJ. O-CAS, a fast and universal method for siderophore detection. J Microbiol Methods 2007; 70:127–131 [View Article] [PubMed]
    [Google Scholar]
  37. Minnikin DE, O’Donnell AG, Goodfellow M, Alderson G, Athalye M et al. An integrated procedure for the extraction of bacterial isoprenoid quinones and polar lipids. J Microbiol Methods 1984; 2:233–241 [View Article]
    [Google Scholar]
  38. Collins MD. Isoprenoidquinones. In Goodfellow M, O’Donnell AG. eds Chemical Methods in Prokaryotic Systematics Chichester: John Wiley & Sons Ltd; 1984 pp 265–309
    [Google Scholar]
  39. Sasser M. Identification of bacteria by gas chromatography of cellular fatty acids. In MIDI Technical Note 101 Newark, DE: MIDI Inc; 1990
    [Google Scholar]
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