1887

Abstract

A Gram-negative, motile, rod-shaped aerobic and alkalogenic bacterium, designated as strain YLCF04, was isolated from chicken faeces. Its growth was optimal at 28 °C (range, 10–40 °C), pH 8 (range, pH 6–9) and in 1 % (w/v) NaCl (range, 0–10 %). It was classified to the genus and was most closely related to CCUG 53761A (97.5 % similarity) based on 16S rRNA gene sequence analysis. Average nucleotide identity and digital DNA–DNA hybridization values between YLCF04 and CCUG 53761A were 76.3 and 18.2 %, respectively. Strain YLCF04 has a genome size of 2.7 Mb with DNA G+C content of 46.3 mol%. Based on its phylogenetic, genomic, phenotypic and biochemical characteristics, strain YLCF04 represents a novel species of the genus , for which the name sp. nov. is proposed. The type strain is YLCF04 (=CCTCC AB 2022359= KCTC 92789).

Funding
This study was supported by the:
  • National Natural Science Foundation of China (Award No. 42207463)
    • Principle Award Recipient: WeiSun
  • Agricultural Key-scientific and Core-technological Project of Shaanxi Province (Award 2023NYGG011)
    • Principle Award Recipient: XunQian
  • National Natural Science Foundation of China (Award No. 42277412)
    • Principle Award Recipient: XunQian
Loading

Article metrics loading...

/content/journal/ijsem/10.1099/ijsem.0.006429
2024-06-19
2024-07-15
Loading full text...

Full text loading...

References

  1. Kämpfer P, Falsen E, Langer S, Lodders N, Busse HJ. Paenalcaligenes hominis gen. nov., sp. nov., a new member of the family Alcaligenaceae. Int J Syst Evol Microbiol 2010; 60:1537–1542 [View Article]
    [Google Scholar]
  2. Lee YY, Lee JK, Park KH, Kim S-Y, Roh SW et al. Paenalcaligenes hermetiae sp. nov., isolated from the larval gut of Hermetia illucens (Diptera: Stratiomyidae), and emended description of the genus Paenalcaligenes. Int J Syst Evol Microbiol 2013; 63:4224–4229 [View Article] [PubMed]
    [Google Scholar]
  3. Moon J-Y, Lim J-M, Ahn J-H, Weon H-Y, Kwon S-W et al. Paenalcaligenes suwonensis sp. nov., isolated from spent mushroom compost. Int J Syst Evol Microbiol 2014; 64:882–886 [View Article] [PubMed]
    [Google Scholar]
  4. Mitzscherling J, MacLean J, Lipus D, Bartholomäus A, Mangelsdorf K et al. Paenalcaligenes niemegkensis sp. nov., a novel species of the family Alcaligenaceae isolated from plastic waste. Int J Syst Evol Microbiol 2022; 71: [View Article] [PubMed]
    [Google Scholar]
  5. Kim DW, Cha CJ. Antibiotic resistome from the One-Health perspective: understanding and controlling antimicrobial resistance transmission. Exp Mol Med 2021; 53:301–309 [View Article] [PubMed]
    [Google Scholar]
  6. Tong CH, Xiao DY, Xie LF, Yang JT, Zhao RN et al. Swine manure facilitates the spread of antibiotic resistome including tigecycline-resistant tet(X) variants to farm workers and receiving environment. Sci Total Environ 2022; 808:152157 [View Article] [PubMed]
    [Google Scholar]
  7. Qian X, Gunturu S, Sun W, Cole JR, Norby B et al. Long-read sequencing revealed cooccurrence, host range, and potential mobility of antibiotic resistome in cow feces. Proc Natl Acad Sci USA 2021; 118:e2024464118 [View Article] [PubMed]
    [Google Scholar]
  8. Sherathiya VN, Schaid MD, Seiler JL, Lopez GC, Lerner TN. GuPPy, a Python toolbox for the analysis of fiber photometry data. Sci Rep 2021; 11:24212 [View Article] [PubMed]
    [Google Scholar]
  9. Koren S, Walenz BP, Berlin K, Miller JR, Bergman NH et al. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res 2017; 27:722–736 [View Article] [PubMed]
    [Google Scholar]
  10. 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] [PubMed]
    [Google Scholar]
  11. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics 2013; 29:1072–1075 [View Article] [PubMed]
    [Google Scholar]
  12. Chklovski A, Parks DH, Woodcroft B, Tyson GW. CheckM2: a rapid, scalable and accurate tool for assessing microbial genome quality using machine learning. Nat Methods 2024; 21:735 [View Article] [PubMed]
    [Google Scholar]
  13. Tatusova T, DiCuccio M, Badretdin A, Chetvernin V, Nawrocki EP et al. NCBI prokaryotic genome annotation pipeline. Nucleic Acids Res 2016; 44:6614–6624 [View Article] [PubMed]
    [Google Scholar]
  14. Powell S, Forslund K, Szklarczyk D, Trachana K, Roth A et al. eggNOG v4.0: nested orthology inference across 3686 organisms. Nucleic Acids Res 2014; 42:D231–D239 [View Article] [PubMed]
    [Google Scholar]
  15. Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M. The KEGG resource for deciphering the genome. Nucleic Acids Res 2004; 32:D277–D280 [View Article] [PubMed]
    [Google Scholar]
  16. Blin K, Shaw S, Augustijn HE, Reitz ZL, Biermann F et al. antiSMASH 7.0: new and improved predictions for detection, regulation, chemical structuresand visualisation. Nucleic Acids Res 2023; 51:W46–W50 [View Article] [PubMed]
    [Google Scholar]
  17. Feldgarden M, Brover V, Gonzalez-Escalona N, Frye JG, Haendiges J et al. AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence. Sci Rep 2021; 11:12728 [View Article] [PubMed]
    [Google Scholar]
  18. Varghese NJ, Mukherjee S, Ivanova N, Konstantinidis KT, Mavrommatis K et al. Microbial species delineation using whole genome sequences. Nucleic Acids Res 2015; 43:6761–6771 [View Article] [PubMed]
    [Google Scholar]
  19. 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]
  20. Kim D, Park S, Chun J. Introducing EzAAI: a pipeline for high throughput calculations of prokaryotic average amino acid identity. J Microbiol 2021; 59:476–480 [View Article] [PubMed]
    [Google Scholar]
  21. 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]
  22. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J et al. BLAST+: architecture and applications. BMC Bioinformatics 2009; 10:421 [View Article] [PubMed]
    [Google Scholar]
  23. Machado RAR, Loulou A, Bhat AH, Mastore M, Terrettaz C et al. Acinetobacter nematophilus sp. nov., Alcaligenes nematophilus sp. nov., Enterobacter nematophilus sp. nov., and Kaistia nematophila sp. nov., isolated from soil-borne nematodes and proposal for the elevation of Alcaligenes faecalis subsp. faecalis, Alcaligenes faecalis subsp. parafaecalis, and Alcaligenes faecalis subsp. phenolicus to the species level. Taxonomy 2023; 3:148–168 [View Article]
    [Google Scholar]
  24. Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA et al. Clustal W and Clustal X version 2.0. Bioinformatics 2007; 23:2947–2948 [View Article] [PubMed]
    [Google Scholar]
  25. 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]
  26. Chaumeil PA, Mussig AJ, Hugenholtz P, Parks DH. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics 2019; 36:1925–1927 [View Article] [PubMed]
    [Google Scholar]
  27. Blin K, Shaw S, Medema MH, Weber T. The antiSMASH database version 4: additional genomes and BGCs, new sequence-based searches and more. Nucleic Acids Res 2024; 52:D586–D589 [View Article] [PubMed]
    [Google Scholar]
  28. Meier-Kolthoff JP, Klenk HP, Göker M. Taxonomic use of DNA G+C content and DNA-DNA hybridization in the genomic age. Int J Syst Evol Microbiol 2014; 64:352–356 [View Article] [PubMed]
    [Google Scholar]
  29. Konstantinidis KT, Tiedje JM. Towards a genome-based taxonomy for prokaryotes. J Bacteriol 2005; 187:6258–6264 [View Article] [PubMed]
    [Google Scholar]
  30. Riesco R, Trujillo ME. Update on the proposed minimal standards for the use of genome data for the taxonomy of prokaryotes. Int J Syst Evol Microbiol 2024; 74:006300 [View Article] [PubMed]
    [Google Scholar]
  31. Barco RA, Garrity GM, Scott JJ, Amend JP, Nealson KH et al. A genus definition for bacteria and Archaea based on a standard genome relatedness index. Mbio 2020; 11:
    [Google Scholar]
  32. Shields P, Cathcart L. Motility test medium protocol. In Am Soc Microbiol 2016 pp 1–10
    [Google Scholar]
  33. Kovacs N. Identification of Pseudomonas pyocyanea by the oxidase reaction. Nature 1956; 178:703 [View Article] [PubMed]
    [Google Scholar]
  34. Brink B. Urease test protocol. In Am Soc Microbiol 2016 pp 1–7
    [Google Scholar]
  35. Dela Cruz TEE, Torres JMO. Gelatin hydrolysis test protocol. Am Soc Microbiol 20161–10
    [Google Scholar]
  36. Hanson A. Oxidative-fermentative test protocol. In Am Soc Microbiol 2016 pp 1–7
    [Google Scholar]
  37. Clinical and Laboratory Standards Institute Performance standards for antimicrobial susceptibility testing, 33rd. edn Wayne, Pa: Clinical and Laboratory Standards Institute; 2023
    [Google Scholar]
  38. EUCAST European Committee on Antimicrobial Susceptibility Testing. Breakpoint tables for373 interpretation of MICs and zone diameters, version 13.1; 2023 https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_13.1_Breakpoint_Tables.pdf
http://instance.metastore.ingenta.com/content/journal/ijsem/10.1099/ijsem.0.006429
Loading
/content/journal/ijsem/10.1099/ijsem.0.006429
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF
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