Skip to main content
SpringerLink
Log in

Vibrio Clade 3.0: New Vibrionaceae Evolutionary Units Using Genome-Based Approach

  • Published:
Current Microbiology Aims and scope Submit manuscript

Abstract

Currently, over 190 species in family Vibrionaceae, including not-yet-cultured taxa, have been described and classified into over nine genera, in which the number of species has doubled compared to the previous vibrio evolutionary update (Vibrio Clade 2.0) (Sawabe et al. 2014). In this study, “Vibrio Clade 3.0,” the second update of the molecular phylogenetic analysis was performed based on nucleotide sequences of eight housekeeping genes (8-HKGs) retrieved from genome sequences, including 22 newly determined genomes. A total of 51 distinct clades were observed, of which 21 clades are newly described. We further evaluated the delineation powers of the clade classification based on nucleotide sequences of 34 single-copy genes and 11 ribosomal protein genes (11-RPGs) retrieved from core-genome sequences; however, the delineation power of 8-HKGs is still high and that gene set can be reliably used for the classification and identification of Vibrionaceae. Furthermore, the 11-RPGs set proved to be useful in identifying uncultured species among metagenome-assembled genome (MAG) and/or single-cell genome-assembled genome (SAG) pools. This study expands the awareness of the diversity and evolutionary history of the family Vibrionaceae and accelerates the taxonomic applications in classifying as not-yet-cultured taxa among MAGs and SAGs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data Availability

The whole genome sequence data obtained in this study was deposited at DDBJ/EMBL/GenBank under BioProject Accession: PRJDB11924.

Code Availability

Not applicable.

References

  1. Thompson FL, Iida T, Swings J (2004) Biodiversity of vibrios. Microbiol Mol Biol Rev 68:403–431. https://doi.org/10.1128/MMBR.68.3.403-431.2004

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Thompson CC, Vicente ACP, Souza RC et al (2009) Genomic taxonomy of vibrios. BMC Evol Biol 9:1–16. https://doi.org/10.1186/1471-2148-9-258

    Article  CAS  Google Scholar 

  3. Gomez-Gil B, Thompson CC, Matsumura Y et al (2014) The famlily Vibrionaceae. The prokaryotes. Springer, Berlin, pp 659–747

    Google Scholar 

  4. Auch AF, von Jan M, Klenk HP et al (2010) Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison. Stand Genom Sci 2:117–134. https://doi.org/10.4056/sigs.531120

    Article  Google Scholar 

  5. Thompson CC, Chimetto L, Edwards RA et al (2013) Microbial genomic taxonomy. BMC Genom. https://doi.org/10.1186/1471-2164-14-913

    Article  Google Scholar 

  6. Sawabe T, Kita-Tsukamoto K, Thompson FL (2007) Inferring the evolutionary history of vibrios by means of multilocus sequence analysis. J Bacteriol 189:7932–7936. https://doi.org/10.1128/JB.00693-07

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Thompson FL, Gomez-Gil B, Vasconcelos ATR, Sawabe T (2007) Multilocus sequence analysis reveals that Vibrio harveyi and V. campbellii are distinct species. Appl Environ Microbiol 73:4279–4285. https://doi.org/10.1128/AEM.00020-07

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. López-Hermoso C, de la Haba RR, Sánchez-Porro C et al (2017) Assessment of multilocus sequence analysis as a valuable tool for the classification of the genus Salinivibrio. Front Microbiol 8:1–14. https://doi.org/10.3389/fmicb.2017.01107

    Article  Google Scholar 

  9. Young JM, Park D-C, Shearman HM, Fargier E (2008) A multilocus sequence analysis of the genus Xanthomonas. Syst Appl Microbiol 31:366–377. https://doi.org/10.1016/j.syapm.2008.06.004

    Article  CAS  PubMed  Google Scholar 

  10. Glaeser SP, Kämpfer P (2015) Multilocus sequence analysis (MLSA) in prokaryotic taxonomy. Syst Appl Microbiol 38:237–245

    Article  CAS  PubMed  Google Scholar 

  11. Cano-Gomez A, Høj L, Owens L, Andreakis N (2011) Multilocus sequence analysis provides basis for fast and reliable identification of Vibrio harveyi-related species and reveals previous misidentification of important marine pathogens. Syst Appl Microbiol 34:561–565. https://doi.org/10.1016/j.syapm.2011.09.001

    Article  CAS  PubMed  Google Scholar 

  12. Guo Y, Zheng W, Rong X, Huang Y (2008) A multilocus phylogeny of the Streptomyces griseus 16S rRNA gene clade: use of multilocus sequence analysis for streptomycete systematics. Int J Syst Evol Microbiol 58:149–159. https://doi.org/10.1099/ijs.0.65224-0

    Article  CAS  PubMed  Google Scholar 

  13. Sawabe T, Ogura Y, Matsumura Y et al (2013) Updating the Vibrio clades defined by multilocus sequence phylogeny: Proposal of eight new clades, and the description of Vibrio tritonius sp. nov. Front Microbiol 4:1–14. https://doi.org/10.3389/fmicb.2013.00414

    Article  Google Scholar 

  14. Medini D, Donati C, Tettelin H et al (2005) The microbial pan-genome. Curr Opin Genet Dev 15:589–594. https://doi.org/10.1016/j.gde.2005.09.006

    Article  CAS  PubMed  Google Scholar 

  15. Tettelin H, Riley D, Cattuto C, Medini D (2008) Comparative genomics: the bacterial pan-genome. Curr Opin Microbiol 11:472–477. https://doi.org/10.1016/j.mib.2008.09.006

    Article  CAS  PubMed  Google Scholar 

  16. Vernikos G, Medini D, Riley DR, Tettelin H (2015) Ten years of pan-genome analyses. Curr Opin Microbiol 23:148–154. https://doi.org/10.1016/j.mib.2014.11.016

    Article  CAS  PubMed  Google Scholar 

  17. Tettelin H, Masignani V, Cieslewicz MJ et al (2005) Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: Implications for the microbial “pan-genome.” Proc Natl Acad Sci 102:13950–13955. https://doi.org/10.1073/pnas.0506758102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Kim Y, Gu C, Kim HU, Lee SY (2020) Current status of pan-genome analysis for pathogenic bacteria. Curr Opin Biotechnol 63:54–62. https://doi.org/10.1016/j.copbio.2019.12.001

    Article  CAS  PubMed  Google Scholar 

  19. Eren AM, Esen ÖC, Quince C et al (2015) Anvi’o: an advanced analysis and visualization platform for ‘omics data. PeerJ 3:e1319. https://doi.org/10.7717/peerj.1319

    Article  PubMed  PubMed Central  Google Scholar 

  20. Delmont TO, Eren AM (2018) Linking pangenomes and metagenomes: the Prochlorococcus metapangenome. PeerJ 6:e4320. https://doi.org/10.7717/peerj.4320

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Sidhu C, Saini MK, Srinivas Tanuku NR, Pinnaka AK (2019) Arenibacter amylolyticus sp. Nov. an amylase-producing bacterium of the family Flavobacteriaceae isolated from marine water in India. Int J Syst Evol Microbiol. https://doi.org/10.1099/ijsem.0.004664

    Article  PubMed  Google Scholar 

  22. Tanaka M, Kumakura D, Mino S et al (2020) Genomic characterization of closely related species in the Rumoiensis clade infers ecogenomic signatures to non-marine environments. Environ Microbiol 22:3205–3217. https://doi.org/10.1111/1462-2920.15062

    Article  CAS  PubMed  Google Scholar 

  23. Aguirre-Sanchez JR, Ibarra-Rodriguez JR, Vega-Lopez IF et al (2021) Genomic signatures of adaptation to natural settings in non-typhoidal Salmonella enterica Serovars Saintpaul, Thompson and Weltevreden. Infect Genet Evol 90:104771. https://doi.org/10.1016/j.meegid.2021.104771

    Article  CAS  PubMed  Google Scholar 

  24. Hug LA, Baker BJ, Anantharaman K et al (2016) A new view of the tree of life. Nat Microbiol 1:16048. https://doi.org/10.1038/nmicrobiol.2016.48

    Article  CAS  PubMed  Google Scholar 

  25. Parks DH, Chuvochina M, Waite DW et al (2018) A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat Biotechnol 36:996. https://doi.org/10.1038/nbt.4229

    Article  CAS  PubMed  Google Scholar 

  26. Hendry TA, Freed LL, Fader D et al (2018) Ongoing transposon-mediated genome reduction in the luminous bacterial symbionts of deep-sea ceratioid anglerfishes. MBio. https://doi.org/10.1128/mBio.01033-18

    Article  PubMed  PubMed Central  Google Scholar 

  27. Baker LJ, Freed LL, Easson CG et al (2019) Diverse deep-sea anglerfishes share a genetically reduced luminous symbiont that is acquired from the environment. Elife. https://doi.org/10.7554/eLife.47606

    Article  PubMed  PubMed Central  Google Scholar 

  28. Collins FWJ, Walsh CJ, Gomez-Sala B et al (2021) The microbiome of deep-sea fish reveals new microbial species and a sparsity of antibiotic resistance genes. Gut Microbes 13:1–13. https://doi.org/10.1080/19490976.2021.1921924

    Article  CAS  PubMed  Google Scholar 

  29. Gould AL, Fritts-Penniman A, Gaisiner A (2021) Museum genomics illuminate the high specificity of a bioluminescent symbiosis for a genus of reef fish. Front Ecol Evol. https://doi.org/10.3389/fevo.2021.630207

    Article  PubMed  PubMed Central  Google Scholar 

  30. Tu Q, He Z, Zhou J (2014) Strain/species identification in metagenomes using genome-specific markers. Nucleic Acids Res 42:e67–e67. https://doi.org/10.1093/nar/gku138

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Tanaka M, Hongyu B, Jiang C et al (2020) Vibrio taketomensis sp. Nov. by genome taxonomy. Syst Appl Microbiol. https://doi.org/10.1016/j.syapm.2019.126048

    Article  PubMed  Google Scholar 

  32. Wick RR, Judd LM, Holt KE (2018) Deepbinner: demultiplexing barcoded oxford nanopore reads with deep convolutional neural networks. PLOS Comput Biol 14:e1006583. https://doi.org/10.1371/journal.pcbi.1006583

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Kajitani R, Yoshimura D, Ogura Y et al (2020) Platanus_B: an accurate de novo assembler for bacterial genomes using an iterative error-removal process. DNA Res. https://doi.org/10.1093/dnares/dsaa014

    Article  PubMed  PubMed Central  Google Scholar 

  34. Wick RR, Judd LM, Gorrie CL, Holt KE (2017) Unicycler: resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput Biol 13:e1005595. https://doi.org/10.1371/journal.pcbi.1005595

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Kolmogorov M, Yuan J, Lin Y, Pevzner PA (2019) Assembly of long, error-prone reads using repeat graphs. Nat Biotechnol 37:540–546. https://doi.org/10.1038/s41587-019-0072-8

    Article  CAS  PubMed  Google Scholar 

  36. Vaser R, Sović I, Nagarajan N, Šikić M (2017) Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res 27:737–746. https://doi.org/10.1101/gr.214270.116

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Walker BJ, Abeel T, Shea T et al (2014) Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE 9:e112963. https://doi.org/10.1371/journal.pone.0112963

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792–1797. https://doi.org/10.1093/nar/gkh340

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Van Dongen S, Abreu-Goodger C (2012) Using MCL to extract clusters from networks. Springer, New York, pp 281–295

    Google Scholar 

  40. Ranwez V, Harispe S, Delsuc F, Douzery EJP (2011) MACSE: multiple alignment of coding sequences accounting for frameshifts and stop codons. PLoS ONE 6:e22594. https://doi.org/10.1371/journal.pone.0022594

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Kumar S, Stecher G, Tamura K (2016) MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol 33:1870–1874. https://doi.org/10.1093/molbev/msw054

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Nei M, Kumar S (2000) Molecular evolution and phylogenetics. Oxford University Press, Oxford

    Google Scholar 

  43. Kumar S, Stecher G, Li M et al (2018) MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 35:1547–1549. https://doi.org/10.1093/molbev/msy096

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Jain C, Rodriguez-R LM, Phillippy AM et al (2018) High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun 9:5114. https://doi.org/10.1038/s41467-018-07641-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Pritchard L, Glover RH, Humphris S et al (2016) Genomics and taxonomy in diagnostics for food security: soft-rotting enterobacterial plant pathogens. Anal Methods 8:12–24. https://doi.org/10.1039/C5AY02550H

    Article  Google Scholar 

  46. Lee I, Ouk Kim Y, Park S-C, Chun J (2016) OrthoANI: an improved algorithm and software for calculating average nucleotide identity. Int J Syst Evol Microbiol 66:1100–1103. https://doi.org/10.1099/ijsem.0.000760

    Article  CAS  PubMed  Google Scholar 

  47. Meier-Kolthoff JP, Göker M, Spröer C, Klenk HP (2013) When should a DDH experiment be mandatory in microbial taxonomy? Arch Microbiol 195:413–418. https://doi.org/10.1007/s00203-013-0888-4

    Article  CAS  PubMed  Google Scholar 

  48. Meier-Kolthoff JP, Auch AF, Klenk H-P, Göker M (2013) Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinform 14:60. https://doi.org/10.1186/1471-2105-14-60

    Article  Google Scholar 

  49. Rodriguez-R LM, Konstantinidis KT (2014) Bypassing cultivation to identify bacterial species. Microbe Mag 9:111–118. https://doi.org/10.1128/microbe.9.111.1

    Article  Google Scholar 

  50. Hettiarachchi SA, Lee S-J, Lee Y et al (2018) Corallibacterium pacifica gen. nov., sp. nov., a novel bacterium of the family Vibrionaceae isolated from Hard Coral. Curr Microbiol 75:835–841. https://doi.org/10.1007/s00284-018-1455-7

    Article  CAS  PubMed  Google Scholar 

  51. Gomez-Gil B, González-Castillo A, Aguilar-Méndez MJ et al (2021) Veronia nyctiphanis gen. nov., sp. nov., Isolated from the Stomach of the Euphausiid Nyctiphanes simplex (Hansen, 1911) in the Gulf of California, and reclassification of Enterovibrio pacificus as Veronia pacifica comb. nov. Curr Microbiol 78:3782–3790. https://doi.org/10.1007/s00284-021-02627-1

    Article  CAS  PubMed  Google Scholar 

  52. Richter M, Rosselló-Móra R (2009) Shifting the genomic gold standard for the prokaryotic species definition. Proc Natl Acad Sci 106:19126–19131. https://doi.org/10.1073/pnas.0906412106

    Article  PubMed  PubMed Central  Google Scholar 

  53. Goris J, Konstantinidis KT, Klappenbach JA et al (2007) DNA–DNA hybridization values and their relationship to whole-genome sequence similarities. Int J Syst Evol Microbiol 57:81–91. https://doi.org/10.1099/ijs.0.64483-0

    Article  CAS  PubMed  Google Scholar 

  54. Kim M, Oh H-S, Park S-C, Chun J (2014) Towards a taxonomic coherence between average nucleotide identity and 16S rRNA gene sequence similarity for species demarcation of prokaryotes. Int J Syst Evol Microbiol 64:346–351. https://doi.org/10.1099/ijs.0.059774-0

    Article  PubMed  Google Scholar 

  55. Ghosh A, Bhadury P (2019) Vibrio chemaguriensis sp. nov., from Sundarbans, Bay of Bengal. Curr Microbiol 76:1118–1127. https://doi.org/10.1007/s00284-019-01731-7

    Article  CAS  PubMed  Google Scholar 

  56. Tan L, Gómez-Betancur I, Guo S et al (2020) Complete genome of Vibrio neocaledonicus CGJ02-2, an active compounds producing bacterium isolated from South China Sea. Curr Microbiol 77:2665–2673. https://doi.org/10.1007/s00284-020-02047-7

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We sincerely thank Tomomi Shimizu for technical assistance. This work was partly supported by KAKEN 19H03041.

Author information

Authors and Affiliations

  1. Laboratory of Microbiology, Faculty of Fisheries Sciences, Hokkaido University, Hakodate, Japan

    Chunqi Jiang, Mami Tanaka, Sayo Nishikawa, Sayaka Mino & Tomoo Sawabe

  2. Departamento de Microbiología y Parasitología, CRETUS & CIBUS-Facultad de Biología, Universidade de Santiago de Compostela, Campus Vida, Santiago de Compostela, España

    Jesús L. Romalde

  3. Institute of Biology and SAGE-COPPE, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil

    Fabiano L. Thompson

  4. CIAD, AC, Mazatlan Unit for Aquaculture and Environmental Management, Mazatlán, México

    Bruno Gomez-Gil

Authors
  1. Chunqi Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mami Tanaka
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sayo Nishikawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sayaka Mino
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jesús L. Romalde
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Fabiano L. Thompson
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Bruno Gomez-Gil
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Tomoo Sawabe
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

CJ conceived, designed and performed the experiments, analyzed the data, visualized the data, and drafted and reviewed the manuscript. MT and SN performed the experiments and reviewed the manuscript. SM, JLR, FLT, and BGG analyzed the data and reviewed the manuscript. TS conceived and designed the experiments and reviewed the manuscript.

Corresponding author

Correspondence to Tomoo Sawabe.

Ethics declarations

Conflict of interests

The authors declare no competing financial interests.

Ethical Approval

Not applicable.

Consent to Participate

Not applicable.

Consent for Publication

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

284_2021_2725_MOESM1_ESM.pdf

Supplementary file1 Figure S1. The rooted Maximum Likelihood bootstrap consensus tree based on a) 8 housekeeping genes and b) 34 single-copy genes. Branches of each clade are marked by different colors (color was set as same as Figure 2). Figure S2. The rooted Maximum Likelihood bootstrap consensus tree based on a) 8 housekeeping genes and b) 11 ribosomal protein genes. Branches of each clade are marked by different colors (color was set as same as Figure 2). Figure S3. Heatmap representation based on the average nucleotide identity (ANI) distance matrix. Dendrogram shows the hierarchical clustering. Species ID is listed in Table S1. Heatmap was visualized with ComplexHeatmap ver. 2.2.0. Figure S4. Heatmap representation based on the average amino identity (AAI) distance matrix. Dendrogram shows the hierarchical clustering. Species ID is listed in Table S1. Clades (over 2 members) were labeled with the same color as Figure 2, asterisks indicate the split clades. Heatmap was visualized with ComplexHeatmap ver. 2.2.0. Figure S5. Gene similarity of a) concatenated gene sets, b) eight housekeeping genes, and c) 16 ribosomal protein genes (bold indicates 11-RPGs set), circles represent different species, red square indicates the median value, and lower gene similarity means higher gene resolution. Figure S6. Concatenated split network based on nucleotide sequences of 16 ribosomal protein genes retrieved from 188 Vibrionaceae species. Gene sequences were concatenated and the tree was reconstructed using the SplitsTree4 ver. 4.14.8. Color was set as same as Figure 1. Figure S7. Focused concatenated split networks for each clade (except for singletons) based on 8-HKGs with E. coli and V. cholerae as outgroups. (PDF 5861 kb)

Supplementary file2 (PDF 236 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jiang, C., Tanaka, M., Nishikawa, S. et al. Vibrio Clade 3.0: New Vibrionaceae Evolutionary Units Using Genome-Based Approach. Curr Microbiol 79, 10 (2022). https://doi.org/10.1007/s00284-021-02725-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00284-021-02725-0

Search

Navigation