Skip to content
1887

INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY logo International Journal of Systematic and Evolutionary Microbiology

Volume 73, Issue 4

subsp. subsp. nov., isolated from entomopathogenic nematodes No Access

Abstract

Four Gram-negative bacterial strains isolated from entomopathogenic nematodes were biochemically and molecularly characterized to determine their taxonomic position. Results of 16S rRNA gene sequencing indicated that they belong to the class , family , genus , and that they are conspecific. The average 16S rRNA gene sequence similarity between the newly isolated strains and the type strain of its more closely related species, T228, is 99.4 %. We therefore selected only one of them, XENO-1, for further molecular characterization using whole genome-based phylogenetic reconstructions and sequence comparisons. Phylogenetic reconstructions show that XENO-1 is closely related to the type strain of , T228, and to several other strains that are thought to belong to this species. To clarify their taxonomic identities, we calculated average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) values. We observed that the ANI and dDDH values between XENO-1 and T228 are 96.3 and 71.2 %, respectively, suggesting that XENO-1 represents a novel subspecies within the species. Noteworthy, the dDDH values between XENO-1 and several other strains are between 68.7 and 70.9 % and ANI values are between 95.8 and 96.4 %, which could be interpreted, in some instances, as that XENO-1 represents a new species. Considering that for taxonomic description the genomic sequences of the type strains are compared, and to avoid future taxonomic conflicts, we therefore propose to assign XENO-1 to a new subspecies within . ANI and dDDH values between XENO-1 and any other of the species with validly published names of the genus are lower than 96 and 70 %, respectively, supporting its novel status. Biochemical tests and genomic comparisons show that XENO-1 exhibit a unique physiological profile that differs from all the species with validly published names and from their more closely related taxa. Based on this, we propose that strain XENO-1 represents a new subspecies within the species, for which we propose the name subsp. subsp. nov, with XENO-1 (=CCM 9244=CCOS 2015) as the type strain.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): biological control agents , genome-based classification , novel species description , polyphasic classification and whole genome sequencing
© 2023 The Authors
Loading

Article metrics loading...

/content/journal/ijsem/10.1099/ijsem.0.005795
2023-04-27
2025-04-30
Loading full text...

Full text loading...

References

  1. Kaya HK, Gaugler R. Entomopathogenic nematodes. Annu Rev Entomol 1993; 38:181–206 [View Article]
     [Google Scholar]
  2. Caldas C, Cherqui A, Pereira A, Simões N. Purification and characterization of an extracellular protease from Xenorhabdus nematophila involved in insect immunosuppression. Appl Environ Microbiol 2002; 68:1297–1304 [View Article] [PubMed]
     [Google Scholar]
  3. Thomas GM, Poinar GO. Xenorhabdus gen. nov., a genus of entomopathogenic, nematophilic bacteria of the family Enterobacteriaceae. Int J Syst Bacteriol 1979; 29:352–360 [View Article]
     [Google Scholar]
  4. Tailliez P, Laroui C, Ginibre N, Paule A, Pagès S et al. Phylogeny of Photorhabdus and Xenorhabdus based on universally conserved protein-coding sequences and implications for the taxonomy of these two genera. Proposal of new taxa: X. vietnamensis sp. nov., P. luminescens subsp. caribbeanensis subsp. nov., P. luminescens subsp. hainanensis subsp. nov., P. temperata subsp. khanii subsp. nov., P. temperata subsp. tasmaniensis subsp. nov., and the reclassification of P. luminescens subsp. thracensis as P. temperata subsp. thracensis comb. nov. Int J Syst Evol Microbiol 2010; 60:1921–1937 [View Article]
     [Google Scholar]
  5. Tailliez P, Pagès S, Ginibre N, Boemare N. New insight into diversity in the genus Xenorhabdus, including the description of ten novel species. Int J Syst Evol Microbiol 2006; 56:2805–2818 [View Article] [PubMed]
     [Google Scholar]
  6. Kuwata R, Qiu L-H, Wang W, Harada Y, Yoshida M et al. Xenorhabdus ishibashii sp. nov., isolated from the entomopathogenic nematode Steinernema aciari. Int J Syst Evol Microbiol 2013; 63:1690–1695 [View Article] [PubMed]
     [Google Scholar]
  7. Ferreira T, van Reenen CA, Endo A, Spröer C, Malan AP et al. Description of Xenorhabdus khoisanae sp. nov., the symbiont of the entomopathogenic nematode Steinernema khoisanae. Int J Syst Evol Microbiol 2013; 63:3220–3224 [View Article] [PubMed]
     [Google Scholar]
  8. Castaneda-Alvarez C, Prodan S, Zamorano A, San-Blas E, Aballay E. Xenorhabdus lircayensis sp. nov., the symbiotic bacterium associated with the entomopathogenic nematode Steinernema unicornum. Int J Syst Evol Microbiol 2021; 71:5151 [View Article] [PubMed]
     [Google Scholar]
  9. Kämpfer P, Tobias NJ, Ke LP, Bode HB, Glaeser SP. Xenorhabdus thuongxuanensis sp. nov. and Xenorhabdus eapokensis sp. nov., isolated from Steinernema species. Int J Syst Evol Microbiol 2017; 67:1107–1114 [View Article] [PubMed]
     [Google Scholar]
  10. 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]
  11. Nishimura Y, Hagiwara A, Suzuki T, Yamanaka S. Xenorhabdus japonicus sp. nov. associated with the nematode Steinernema kushidai. World J Microbiol Biotechnol 1994; 10:207–210 [View Article] [PubMed]
     [Google Scholar]
  12. Lengyel K, Lang E, Fodor A, Szállás E, Schumann P et al. Description of four novel species of Xenorhabdus, family Enterobacteriaceae: Xenorhabdus budapestensis sp. nov., Xenorhabdus ehlersii sp. nov., Xenorhabdus innexi sp. nov., and Xenorhabdus szentirmaii sp. nov. Syst Appl Microbiol 2005; 28:115–122 [View Article]
     [Google Scholar]
  13. Somvanshi VS, Lang E, Ganguly S, Swiderski J, Saxena AK et al. A novel species of Xenorhabdus, family Enterobacteriaceae: Xenorhabdus indica sp. nov., symbiotically associated with entomopathogenic nematode Steinernema thermophilum Ganguly and Singh, 2000. Syst Appl Microbiol 2006; 29:519–525 [View Article]
     [Google Scholar]
  14. Akhurst RJ, Boemare NE. A non-luminescent strain of Xenorhabdus luminescens (Enterobacteriaceae). Microbiology 1986; 132:1917–1922 [View Article]
     [Google Scholar]
  15. Akhurst RJ, Boemare NE. A numerical taxonomic study of the genus Xenorhabdus (Enterobacteriaceae) and proposed elevation of the subspecies of X. nematophilus to species. J Gen Microbiol 1988; 134:1835–1845 [View Article]
     [Google Scholar]
  16. Akhurst RJ. Taxonomic study of Xenorhabdus, a genus of bacteria symbiotically associated with insect pathogenic nematodes. Int J Syst Bacteriol 1983; 33:38–45 [View Article]
     [Google Scholar]
  17. Tailliez P, Pagès S, Edgington S, Tymo LM, Buddie AG. Description of Xenorhabdus magdalenensis sp. nov., the symbiotic bacterium associated with Steinernema australe. Int J Syst Evol Microbiol 2012; 62:1761–1765 [View Article] [PubMed]
     [Google Scholar]
  18. Poinar GO, Thomas GM. A new bacterium, Achromobacter nematophilus sp. nov. (Achromobacteriaceae: Eubacteriales) associated with a nematode. Int J Syst Evol Microbiol 1965; 15:249–252 [View Article]
     [Google Scholar]
  19. Fallet P, Machado RAR, Toepfer S, Ye W, Kajuga J et al. A rwandan survey of entomopathogenic nematodes that can potentially be used to control the fall armyworm. IOBC-WPRS Bulletin 2020; 150:87–90
     [Google Scholar]
  20. Yan X, Waweru B, Qiu X, Hategekimana A, Kajuga J et al. New entomopathogenic nematodes from semi-natural and small-holder farming habitats of Rwanda. Biocontrol Science and Technology 2016; 26:820–834 [View Article]
     [Google Scholar]
  21. Machado RAR, Bhat AH, Abolafia J, Shokoohi E, Fallet P et al. Steinernema africanum n. sp. (Rhabditida, Steinernematidae), a new entomopathogenic nematode species isolated in the Republic of Rwanda. J Nematol 2022; 54:e2022–1 [View Article]
     [Google Scholar]
  22. Fukruksa C, Yimthin T, Suwannaroj M, Muangpat P, Tandhavanant S et al. Isolation and identification of Xenorhabdus and Photorhabdus bacteria associated with entomopathogenic nematodes and their larvicidal activity against Aedes aegypti. Parasit Vectors 2017; 10:440 [View Article]
     [Google Scholar]
  23. Marchesi JR, Sato T, Weightman AJ, Martin TA, Fry JC et al. Design and evaluation of useful bacterium-specific PCR primers that amplify genes coding for bacterial 16S rRNA. Appl Environ Microbiol 1998; 64:795–799 [View Article] [PubMed]
     [Google Scholar]
  24. Hill V, Kuhnert P, Erb M, Machado RAR. Identification of Photorhabdus symbionts by MALDI-TOF MS. Microbiology 2020; 166:522–530 [View Article]
     [Google Scholar]
  25. Hall T. BioEdit: a user-friendly biological sequence alignment editor and analysis program for windows 95/98/NT. Nucleic Acids Symp 1999
     [Google Scholar]
  26. Seemann T. Barrnap 0.7: rapid ribosomal RNA prediction. https://github.com/tseemann/barrnap 2013
  27. Kumar S, Stecher G, Tamura K. MEGA7: Molecular Evolutionary Genetics Analysis version 7.0 for bigger datasets. Mol Biol Evol 2016; 33:1870–1874 [View Article]
     [Google Scholar]
  28. Hasegawa M, Kishino H, Yano T. Dating of the human-ape splitting by a molecular clock of mitochondrial DNA. J Mol Evol 1985; 22:160–174 [View Article] [PubMed]
     [Google Scholar]
  29. Nei M, Kumar S. Molecular Evolution and Phylogenetics Oxford University Press; 2000
     [Google Scholar]
  30. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 2004; 32:1792–1797 [View Article] [PubMed]
     [Google Scholar]
  31. Chevenet F, Brun C, Bañuls A-L, Jacq B, Christen R. TreeDyn: towards dynamic graphics and annotations for analyses of trees. BMC Bioinformatics 2006; 7:439 [View Article] [PubMed]
     [Google Scholar]
  32. Letunic I, Bork P. Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res 2016; 44:W242–5 [View Article]
     [Google Scholar]
  33. Machado RAR, Wüthrich D, Kuhnert P, Arce CCM, Thönen L et al. Whole-genome-based revisit of Photorhabdus phylogeny: proposal for the elevation of most Photorhabdus subspecies to the species level and description of one novel species Photorhabdus bodei sp. nov., and one novel subspecies Photorhabdus laumondii subsp. clarkei subsp. nov. Int J Syst Evol Microbiol 2018; 68:2664–2681 [View Article]
     [Google Scholar]
  34. Machado RAR, Bhat AH, Abolafia J, Muller A, Bruno P et al. Multi-locus phylogenetic analyses uncover species boundaries and reveal the occurrence of two new entomopathogenic nematode species, Heterorhabditis ruandica n. sp. and Heterorhabditis zacatecana n. sp. J Nematol 2021; 53:e2021-89 [View Article]
     [Google Scholar]
  35. Petit RA, Read TD. Bactopia: a flexible pipeline for complete analysis of bacterial genomes. mSystems 2020; 5:e00190-20 [View Article]
     [Google Scholar]
  36. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article] [PubMed]
     [Google Scholar]
  37. 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]
  38. Walker BJ, Abeel T, Shea T, Priest M, Abouelliel A et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS One 2014; 9:e112963 [View Article]
     [Google Scholar]
  39. Hyatt D, Chen G-L, Locascio PF, Land ML, Larimer FW et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 2010; 11:1–11 [View Article] [PubMed]
     [Google Scholar]
  40. Steinegger M, Söding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat Biotechnol 2017; 35:1026–1028 [View Article] [PubMed]
     [Google Scholar]
  41. van Dongen SM. PhD Thesis: Graph clustering by flow simulation University of Utrecht, Utrecht University Repository; 2000
     [Google Scholar]
  42. van Dongen S, Abreu-Goodger C. Using MCL to extract clusters from networks. Methods Mol Biol 2012; 804:281–295 [View Article]
     [Google Scholar]
  43. Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 2013; 30:772–780 [View Article]
     [Google Scholar]
  44. Stamatakis A. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 2006; 22:2688–2690 [View Article] [PubMed]
     [Google Scholar]
  45. Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 2014; 30:1312–1313 [View Article] [PubMed]
     [Google Scholar]
  46. 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]
  47. Meier-Kolthoff JP, Hahnke RL, Petersen J, Scheuner C, Michael V et al. Complete genome sequence of DSM 30083(T), the type strain (U5/41(T)) of Escherichia coli, and a proposal for delineating subspecies in microbial taxonomy. Stand Genomic Sci 2014; 9:2 [View Article] [PubMed]
     [Google Scholar]
  48. Auch AF, von Jan M, Klenk H-P, Göker M. Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison. Stand Genomic Sci 2010; 2:117–134 [View Article] [PubMed]
     [Google Scholar]
  49. Auch AF, Klenk H-P, Göker M. Standard operating procedure for calculating genome-to-genome distances based on high-scoring segment pairs. Stand Genomic Sci 2010; 2:142–148 [View Article] [PubMed]
     [Google Scholar]
  50. Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun 2018; 9:5114 [View Article] [PubMed]
     [Google Scholar]
  51. Tindall BJ. Proposed modifications to Rule 40d of the International Code of Nomenclature of Prokaryotes. Int J Syst Evol Microbiol 2019; 69:1519–1520 [View Article] [PubMed]
     [Google Scholar]
  52. Parker CT, Tindall BJ, Garrity GM. International Code of Nomenclature of Prokaryotes: Prokaryotic Code (2008 Revision). Int J Syst Evol Microbiol 2019; 69:S1–S111 [View Article]
     [Google Scholar]
  53. Chen C-Y, Clark CG, Langner S, Boyd DA, Bharat A et al. Detection of antimicrobial resistance using proteomics and the comprehensive antibiotic resistance database: a case study. Proteomics Clin Appl 2020; 14:e1800182 [View Article]
     [Google Scholar]
  54. 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]
     [Google Scholar]
  55. Guitor AK, Raphenya AR, Klunk J, Kuch M, Alcock B et al. Capturing the resistome: a targeted capture method to reveal antibiotic resistance determinants in metagenomes. Antimicrob Agents Chemother 2019; 64:e01324-19 [View Article]
     [Google Scholar]
  56. Tsang K, Speicher D, McArthur A. Pathogen taxonomy updates at the comprehensive antibiotic resistance database: implications for molecular epidemiology. Life Sciences 2019 [View Article]
     [Google Scholar]
  57. McArthur AG, Waglechner N, Nizam F, Yan A, Azad MA et al. The comprehensive antibiotic resistance database. Antimicrob Agents Chemother 2013; 57:3348–3357 [View Article] [PubMed]
     [Google Scholar]
  58. Jia B, Raphenya AR, Alcock B, Waglechner N, Guo P et al. CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database. Nucleic Acids Res 2017; 45:D566–D573 [View Article]
     [Google Scholar]
  59. 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]
     [Google Scholar]
  60. Chen L, Zheng D, Liu B, Yang J, Jin Q. VFDB 2016: hierarchical and refined dataset for big data analysis--10 years on. Nucleic Acids Res 2016; 44:D694–7 [View Article]
     [Google Scholar]
  61. Chen L, Yang J, Yu J, Yao Z, Sun L et al. VFDB: a reference database for bacterial virulence factors. Nucleic Acids Res 2005; 33:D325–8 [View Article]
     [Google Scholar]
  62. Chen L, Xiong Z, Sun L, Yang J, Jin Q. VFDB 2012 update: toward the genetic diversity and molecular evolution of bacterial virulence factors. Nucleic Acids Res 2012; 40:D641–5 [View Article]
     [Google Scholar]
  63. Yang J, Chen L, Sun L, Yu J, Jin Q. VFDB 2008 release: an enhanced web-based resource for comparative pathogenomics. Nucleic Acids Res 2008; 36:D539–42 [View Article]
     [Google Scholar]
  64. Blin K, Shaw S, Kloosterman AM, Charlop-Powers Z, van Wezel GP et al. antiSMASH 6.0: improving cluster detection and comparison capabilities. Nucleic Acids Res 2021; 49:W29–W35 [View Article]
     [Google Scholar]
  65. Blin K, Shaw S, Steinke K, Villebro R, Ziemert N et al. antiSMASH 5.0: updates to the secondary metabolite genome mining pipeline. Nucleic Acids Res 2019; 47:W81–W87 [View Article]
     [Google Scholar]
/content/journal/ijsem/10.1099/ijsem.0.005795
Loading
Xenorhabdus bovienii subsp. africana subsp. nov., isolated from Steinernema africanum entomopathogenic nematodes
Int J Syst Evol Microbiol 73, 005795 (2023); https://doi.org/10.1099/ijsem.0.005795
/content/journal/ijsem/10.1099/ijsem.0.005795
/content/journal/ijsem/10.1099/ijsem.0.005795
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Most cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error