1887

Abstract

During an investigation of microbes associated with arthropods living in decaying coconut trees, a isolate, Milli4, was cultured from the digestive tract of the common Asian millipede, . Sequence analysis of 16S rRNA and genes found that Milli4 was closely related but not identical to Esp-1, B13 and CCA1. Whole genome sequencing suggested that this isolate represents a new species, with average nucleotide identity (OrthoANIu) values of around 83.9–87.7% with its closest relatives. Genome-to-genome distance calculations between Milli4 and its closest relatives also suggested they are distinct species. The genomic DNA G+C content of Milli4 was approximately 65.0 mol%. Phenotypic and chemotaxonomic characterization and fatty acid methyl ester analysis was performed on Milli4 and its related type strains. Based on these data, the new species sp. nov. is proposed, and the type strain is Milli4 (=BCRC 81294=JCM 34414=CIP 111980).

Funding
This study was supported by the:
  • Ministry of Science and Technology, Taiwan (Award 109-2311-B-002-016-MY3)
    • Principle Award Recipient: MatanShelomi
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2021-10-27
2024-07-17
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References

  1. Peix A, Ramírez-Bahena M-H, Velázquez E. The current status on the taxonomy of Pseudomonas revisited: An update. Infect Genet Evol 2018; 57:106–116 [View Article] [PubMed]
    [Google Scholar]
  2. Moore ERB, Tindall BJ, Martins dos Santos VAP, Pieper DH, Ramos JL et al. Nonmedical: Pseudomonas. Dworkin M, Falkow S, Rosenberg E, Schleifer KH, Stackebrandt E. eds In The Prokaryotes New York: Springer; 2006 pp 646–703
    [Google Scholar]
  3. Migula N. Arbeiten Aus dem Bakteriologischen. Inst Technischen Hochschule Karlsruhe 1894; 1:235–238
    [Google Scholar]
  4. Mulet M, Gomila M, Lemaitre B, Lalucat J, García-Valdés E. Taxonomic characterisation of Pseudomonas strain L48 and formal proposal of Pseudomonas entomophila sp. nov. Syst Appl Microbiol 2012; 35:145–149 [View Article] [PubMed]
    [Google Scholar]
  5. Nowell RW, Laue BE, Sharp PM, Green S. Comparative genomics reveals genes significantly associated with woody hosts in the plant pathogen Pseudomonas syringae. Mol Plant Pathol 2016; 17:1409–1424 [View Article] [PubMed]
    [Google Scholar]
  6. Menéndez E, Ramírez-Bahena MH, Fabryová A, Igual JM, Benada O et al. Pseudomonas coleopterorum sp. nov., a cellulase-producing bacterium isolated from the bark beetle Hylesinus fraxini. Int J Syst Evol Microbiol 2015; 65:2852–2858 [View Article] [PubMed]
    [Google Scholar]
  7. Anwar N, Abaydulla G, Zayadan B, Abdurahman M, Hamood B et al. Pseudomonas populi sp. nov., an endophytic bacterium isolated from Populus euphratica. Int J Syst Evol Microbiol 2016; 66:1419–1425 [View Article] [PubMed]
    [Google Scholar]
  8. Hu X, Yu J, Wang C, Chen H. Cellulolytic bacteria associated with the gut of Dendroctonus armandi larvae (Coleoptera: Curculionidae: Scolytinae). Forests 2014; 5:455–465 [View Article]
    [Google Scholar]
  9. Bansal R, Hulbert SH, Reese JC, Whitworth RJ, Stuart JJ et al. Pyrosequencing reveals the predominance of Pseudomonadaceae in gut microbiome of a gall midge. Pathogens 2014; 3:459–472 [View Article] [PubMed]
    [Google Scholar]
  10. Zhang F, Huang YH, Liu SZ, Zhang L, Li BT et al. Pseudomonas reactans, a bacterial strain isolated from the intestinal flora of Blattella germanica with anti-Beauveria bassiana activity. Environ Entomol 2013; 42:453–459 [View Article] [PubMed]
    [Google Scholar]
  11. Shelomi M, Chen M-J. Culturing-enriched metabarcoding analysis of the Oryctes rhinoceros gut microbiome. Insects 2020; 11:e782 [View Article] [PubMed]
    [Google Scholar]
  12. Kasana RC, Salwan R, Dhar H, Dutt S, Gulati A. A rapid and easy method for the detection of microbial cellulases on agar plates using Gram’s iodine. Curr Microbiol 2008; 57:503–507 [View Article] [PubMed]
    [Google Scholar]
  13. Ki J-S, Zhang W, Qian P-Y. Discovery of Marine bacillus species by 16S rRNA and rpob comparisons and their usefulness for species identification. J Microbiol Methods 2009; 77:48–57 [View Article] [PubMed]
    [Google Scholar]
  14. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic Local Alignment Search Tool. J Mol Biol 1990; 215:403–410 [View Article] [PubMed]
    [Google Scholar]
  15. 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]
  16. Bolger AM, Lohse M, Usadel B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article] [PubMed]
    [Google Scholar]
  17. 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]
  18. Prjibelski A, Antipov D, Meleshko D, Lapidus A, Korobeynikov A. Using spades de novo assembler. Curr Protoc Bioinformatics 2020; 70:e102 [View Article] [PubMed]
    [Google Scholar]
  19. Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv preprint 201313033997
    [Google Scholar]
  20. Klockgether J, Cramer N, Wiehlmann L, Davenport CF, Tümmler B. Pseudomonas aeruginosa genomic structure and diversity. Front Microbiol 2011; 2:150 [View Article] [PubMed]
    [Google Scholar]
  21. Seemann T. PROKKA: Rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article] [PubMed]
    [Google Scholar]
  22. Yoon S-H, Ha S-M, 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]
  23. Meier-Kolthoff JP, Auch AF, Klenk H-P, Göker M. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinformatics 2013; 14:60 [View Article] [PubMed]
    [Google Scholar]
  24. Na S-I, Kim YO, Yoon S-H, Ha S-M, 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. Alcock BP, Raphenya AR, Lau TTY, Tsang KK, Bouchard M et al. CARD 2020: Antibiotic resistome surveillance with the comprehensive antibiotic Resistance database. Nucleic Acids Res 2020; 48:D517–D525 [View Article] [PubMed]
    [Google Scholar]
  26. Liu B, Zheng D, Jin Q, Chen L, Yang J. VFDB 2019: A comparative pathogenomic platform with an interactive web interface. Nucleic Acids Res 2019; 47:D687–D692 [View Article] [PubMed]
    [Google Scholar]
  27. Katoh K, Rozewicki J, Yamada KD. MAFFT online service: Multiple sequence alignment, interactive sequence choice and visualization. Brief Bioinform 2019; 20:1160–1166 [View Article] [PubMed]
    [Google Scholar]
  28. Katoh K, Kuma K, Toh H, Miyata T. MAFFT version 5: Improvement in accuracy of multiple sequence alignment. Nucleic Acids Res 2005; 33:511–518 [View Article] [PubMed]
    [Google Scholar]
  29. Trifinopoulos J, Nguyen L-T, von Haeseler A, Minh BQ. W-IQ-TREE: A fast online phylogenetic tool for maximum likelihood analysis. Nucleic Acids Res 2016; 44:W232–5 [View Article] [PubMed]
    [Google Scholar]
  30. Nguyen L-T, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: A fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol 2015; 32:268–274 [View Article] [PubMed]
    [Google Scholar]
  31. Hoang DT, Chernomor O, von Haeseler A, Minh BQ, Vinh LS. Ufboot2: Improving the ultrafast bootstrap approximation. Mol Biol Evol 2018; 35:518–522 [View Article] [PubMed]
    [Google Scholar]
  32. Kalyaanamoorthy S, Minh BQ, Wong TKF, von Haeseler A, Jermiin LS. Modelfinder: Fast model selection for accurate phylogenetic estimates. Nat Methods 2017; 14:587–589 [View Article] [PubMed]
    [Google Scholar]
  33. Sazci A, Erenler K, Radford A. Detection of cellulolytic fungi by using Congo red as an indicator: A comparative study with the dinitrosalicyclic acid reagent method. J Appl Bacteriol 1986; 61:559–562 [View Article]
    [Google Scholar]
  34. Akita H, Kimura Z-I, Hoshino T. Pseudomonas humi sp. nov., isolated from leaf soil. Arch Microbiol 2019; 201:245–251 [View Article] [PubMed]
    [Google Scholar]
  35. Wang Y-N, He W-H, He H, Du X, Jia B et al. Pseudomonas nitritireducens sp. nov., a nitrite reduction bacterium isolated from wheat soil. Arch Microbiol 2012; 194:809–813 [View Article] [PubMed]
    [Google Scholar]
  36. Sasser M. Identification of Bacteria by Gas Chromatography of Cellular Fatty Acids, MIDI technical note 101. Newark, DE: 1990
    [Google Scholar]
  37. Schmalbach P. Affective Response to Exercise, Affective Style, Perceived Competence, and Physical Activity Behavior in Adolescents University of California, Irvine; Irvine, CA: 2014
    [Google Scholar]
  38. Lahham S, Schmalbach P, Wilson SP, Ludeman L, Subeh M et al. Prospective evaluation of point-of-care ultrasound for pre-procedure identification of landmarks versus traditional palpation for lumbar puncture. World J Emerg Med 2016; 7:173–177 [View Article] [PubMed]
    [Google Scholar]
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