1887

Abstract

Two Gram-stain-negative, non-spore-forming, rod-shaped, and obligately aerobic bacteria, designated strains CX-624 and cx-311, were isolated from soil samples in Qinghai Province, China. The two strains grew best at 28 °C on the plate with Tryptone soya agar (TSA). Cells formed circular, convex, translucent, smooth, and orange colonies with approximately 1.0 mm diameter after 2 days of incubation on TSA at 28 °C. The strains were oxidase-negative and catalase-positive. The predominant cellular fatty acids were iso-C and anteiso-C, and major polar lipids included phosphatidylethanolamine, an unidentified aminophospholipid, four unidentified lipids and an aminolipid. MK-6 was the sole menaquinone in strain CX-624. Comparative analysis of the nearly full-length 16S rRNA gene sequences showed strains CX-624 and cx-311 were member of the family , with the highest similarity to H38 (96.66 %), DSM 18015 (96.59 %), and DSM 18014 (96.53 %). Both phylogenetic analysis of the 16S rRNA gene and 177 core genes revealed that strains CX-624 and cx-311 formed an independent clade. Average nucleotide identity values (< 72.64 %), average amino-acid identity values (<72.61 %) and digital DNA–DNA hybridization (< 21.10 %) indicated that the strains CX-624 and cx-311 should constitute a novel genus. The DNA G+C contents of strains CX-624 and cx-311 were 43.0 mol% and 42.7 mol%. According to the data obtained in this study, strain CX-624 represents a novel species belonging to a novel genus of the , for which the name gen. nov., sp. nov. is proposed. The type strain is CX-624 (=GDMCC 1.1714 = JCM 33925).

Loading

Article metrics loading...

/content/journal/ijsem/10.1099/ijsem.0.006020
2023-10-31
2024-05-08
Loading full text...

Full text loading...

References

  1. Bernardet J-F, Nakagawa Y, Holmes B. Proposed minimal standards for describing new taxa of the family Flavobacteriaceae and emended description of the family. Int J Syst Evol Microbiol 2002; 52:1049–1070 [View Article] [PubMed]
    [Google Scholar]
  2. García-López M, Meier-Kolthoff JP, Tindall BJ, Gronow S, Woyke T et al. Analysis of 1,000 type-strain genomes improves taxonomic classification of Bacteroidetes. Front Microbiol 2019; 10:2083 [View Article] [PubMed]
    [Google Scholar]
  3. Nicholson AC, Gulvik CA, Whitney AM, Humrighouse BW, Bell ME et al. Division of the genus Chryseobacterium: observation of discontinuities in amino acid identity values, a possible consequence of major extinction events, guides transfer of nine species to the genus Epilithonimonas, eleven species to the genus Kaistella, and three species to the genus Halpernia gen. nov., with description of Kaistella daneshvariae sp. nov. and Epilithonimonas vandammei sp. nov. derived from clinical specimens. Int J Syst Evol Microbiol 2020; 70:4432–4450 [View Article] [PubMed]
    [Google Scholar]
  4. Charimba G, Jooste P, Albertyn J, Hugo C. Chryseobacterium carnipullorum sp. nov., isolated from raw chicken. Int J Syst Evol Microbiol 2013; 63:3243–3249 [View Article] [PubMed]
    [Google Scholar]
  5. Gallego V, García MT, Ventosa A. Chryseobacterium hispanicum sp. nov., isolated from the drinking water distribution system of Sevilla, Spain. Int J Syst Evol Microbiol 2006; 56:1589–1592 [View Article] [PubMed]
    [Google Scholar]
  6. Kämpfer P, Busse H-J, McInroy JA, Glaeser SP. Chryseobacterium arachidiradicis sp. nov., isolated from the geocarposphere (soil around the peanut) of very immature peanuts (Arachis hypogaea). Int J Syst Evol Microbiol 2015; 65:2179–2186 [View Article] [PubMed]
    [Google Scholar]
  7. Kook M, Son H-M, Ngo HTT, Yi T-H. Chryseobacterium camelliae sp. nov., isolated from green tea. Int J Syst Evol Microbiol 2014; 64:851–857 [View Article] [PubMed]
    [Google Scholar]
  8. Loch TP, Faisal M. Chryseobacterium aahli sp. nov., isolated from lake trout (Salvelinus namaycush) and brown trout (Salmo trutta), and emended descriptions of Chryseobacterium ginsenosidimutans and Chryseobacterium gregarium. Int J Syst Evol Microbiol 2014; 64:1573–1579 [View Article] [PubMed]
    [Google Scholar]
  9. Kämpfer P, Vaneechoutte M, Lodders N, De Baere T, Avesani V et al. Description of Chryseobacterium anthropi sp. nov. to accommodate clinical isolates biochemically similar to Kaistella koreensis and Chryseobacterium haifense, proposal to reclassify Kaistella koreensis as Chryseobacterium koreense comb. nov. and emended description of the genus Chryseobacterium. Int J Syst Evol Microbiol 2009; 59:2421–2428 [View Article] [PubMed]
    [Google Scholar]
  10. Holmes B, Steigerwalt AG, Nicholson AC. DNA-DNA hybridization study of strains of Chryseobacterium, Elizabethkingia and Empedobacter and of other usually indole producing non-fermenters of CDC groups IIc, IIe, IIh and IIi, mostly from human clinical sources, and proposals of Chryseobacterium bernardetii sp. nov., Chryseobacterium carnis sp. nov., Chryseobacterium lactis sp. nov., Chryseobacterium nakagawai sp. nov. and Chryseobacterium taklimakanense comb. nov. Int J Syst Evol Microbiol 2013; 63:4639–4662 [View Article]
    [Google Scholar]
  11. Montero-Calasanz MDC, Göker M, Rohde M, Spröer C, Schumann P et al. Chryseobacterium hispalense sp. nov., a plant-growth-promoting bacterium isolated from a rainwater pond in an olive plant nursery, and emended descriptions of Chryseobacterium defluvii, Chryseobacterium indologenes, Chryseobacterium wanjuense and Chryseobacterium gregarium. Int J Syst Evol Microbiol 2013; 63:4386–4395 [View Article] [PubMed]
    [Google Scholar]
  12. Vaneechoutte M, Kämpfer P, De Baere T, Avesani V, Janssens M et al. Chryseobacterium hominis sp. nov., to accommodate clinical isolates biochemically similar to CDC groups II-h and II-c. Int J Syst Evol Microbiol 2007; 57:2623–2628 [View Article] [PubMed]
    [Google Scholar]
  13. 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]
  14. Myers EW, Miller W. Optimal alignments in linear space. Bioinformatics 1988; 4:11–17 [View Article]
    [Google Scholar]
  15. Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 1994; 22:4673–4680 [View Article] [PubMed]
    [Google Scholar]
  16. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: Molecular Evolutionary Genetics Analysis across computing platforms. Mol Biol Evol 2018; 35:1547–1549 [View Article] [PubMed]
    [Google Scholar]
  17. Kimura M. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol 1980; 16:111–120 [View Article] [PubMed]
    [Google Scholar]
  18. 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] [PubMed]
    [Google Scholar]
  19. Price MN, Dehal PS, Arkin AP. FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol Biol Evol 2009; 26:1641–1650 [View Article] [PubMed]
    [Google Scholar]
  20. Cashion P, Holder-Franklin MA, McCully J, Franklin M. A rapid method for the base ratio determination of bacterial DNA. Anal Biochem 1977; 81:461–466 [View Article] [PubMed]
    [Google Scholar]
  21. Berlin K, Koren S, Chin C-S, Drake JP, Landolin JM et al. Corrigendum: assembling large genomes with single-molecule sequencing and locality-sensitive hashing. Nat Biotechnol 2015; 33:623–630 [View Article] [PubMed]
    [Google Scholar]
  22. Li D, Liu C-M, Luo R, Sadakane K, Lam T-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 2015; 31:1674–1676 [View Article] [PubMed]
    [Google Scholar]
  23. Lomsadze A, Gemayel K, Tang S, Borodovsky M. Modeling leaderless transcription and atypical genes results in more accurate gene prediction in prokaryotes. Genome Res 2018; 28:1079–1089 [View Article] [PubMed]
    [Google Scholar]
  24. 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]
  25. Rodriguez-R LM, Konstantinidis KT. Bypassing cultivation to identify bacterial species. Microbe Magazine 2014; 9:111–118 [View Article]
    [Google Scholar]
  26. Aziz RK, Bartels D, Best AA, DeJongh M, Disz T et al. The RAST server: rapid annotations using subsystems technology. BMC Genomics 2008; 9:75 [View Article] [PubMed]
    [Google Scholar]
  27. Zhang H, Yohe T, Huang L, Entwistle S, Wu P et al. dbCAN2: a meta server for automated carbohydrate-active enzyme annotation. Nucleic Acids Res 2018; 46:W95–W101 [View Article] [PubMed]
    [Google Scholar]
  28. Mogadem A, Almamary MA, Mahat NA, Jemon K, Ahmad WA et al. Antioxidant activity evaluation of FlexirubinType pigment from Chryseobacterium artocarpi CECT 8497 and related docking study. Molecules 2021; 26:979 [View Article] [PubMed]
    [Google Scholar]
  29. M. S Microbial identification by gas chromatographic analysis of fatty acid methyl esters (GC FAME). In Technical Note vol 101 2009 pp 1–6
    [Google Scholar]
  30. Collins MD, Jones D. Distribution of isoprenoid quinone structural types in bacteria and their taxonomic implication. Microbiol Rev 1981; 45:316–354 [View Article] [PubMed]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/ijsem/10.1099/ijsem.0.006020
Loading
/content/journal/ijsem/10.1099/ijsem.0.006020
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