Skip to content
1887

Abstract

An anaerobic isolate, designated me31, was isolated from pit mud in Yibin, Sichuan Province, PR China. Phylogenetic results based on 16S rRNA gene sequence showed that strain me31 belongs to the family , and the most closely related isolated relatives were SYSU GA16112 (93.65%) and JNU-WLY501 (93.22%). The DNA G+C content was 44.26 mol%. The ANI and AAI values between strain me31 and the closely related strains were 69.25–71.18% and 69.59–71.15%, respectively. Cells of strain me31 were Gram-stain-negative, rod-shaped and non-motile. Growth of strain me31 was observed at 25–37 °C, pH 6.0–8.0 and a salt tolerance range of 0–1.0% (w/v). The predominant respiratory quinone was MK-9. The major fatty acids were anteiso-C, anteiso-C and C 2OH. The polar lipids of strain me31 were found to consist of phosphatidylethanolamine, three unidentified phospholipids, three unidentified phosphoglycolipids, one unidentified phosphoglycolipid, one unidentified lipid, two unidentified glycolipids and one aminophosphoglycolipid. According to the results of morphological, physiological, biochemical, chemotaxonomic, genotypic and phylogenetic analysis, strain me31 represents a novel species of a novel genus of the family , for which the name gen. nov., sp. nov. is proposed. The type strain is me31 (=GDMCC 1.4237=KCTC 25756=WMCC 10035).

Funding
This study was supported by the:
  • Tianfu Ten Thousand People Program-Tianfu Science and Technology Elite Project (Award TFJY2021001)
    • Principal Award Recipient: JiaZheng
  • Yibin Science and Technology Planning Program (Award 2023CG001)
    • Principal Award Recipient: JiaZheng
Loading

Article metrics loading...

/content/journal/ijsem/10.1099/ijsem.0.006702
2025-03-06
2026-04-17

Metrics

Loading full text...

Full text loading...

References

  1. 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]
  2. Pasalari H, Gholami M, Rezaee A, Esrafili A, Farzadkia M. Perspectives on microbial community in anaerobic digestion with emphasis on environmental parameters: a systematic review. Chemosphere 2021; 270:128618 [View Article] [PubMed]
    [Google Scholar]
  3. Larsbrink J, McKee LS. Bacteroidetes bacteria in the soil: glycan acquisition, enzyme secretion, and gliding motility. Adv Appl Microbiol 2020; 110:63–98 [View Article] [PubMed]
    [Google Scholar]
  4. Flint HJ, Scott KP, Duncan SH, Louis P, Forano E. Microbial degradation of complex carbohydrates in the gut. Gut Microbes 2012; 3:289–306 [View Article]
    [Google Scholar]
  5. Pan X, Raaijmakers JM, Carrión VJ. Importance of Bacteroidetes in host-microbe interactions and ecosystem functioning. Trends Microbiol 2023; 31:959–971 [View Article] [PubMed]
    [Google Scholar]
  6. Tao Y, Li J, Rui J, Xu Z, Zhou Y et al. Prokaryotic communities in pit mud from different-aged cellars used for the production of Chinese strong-flavored liquor. Appl Environ Microbiol 2014; 80:2254–2260 [View Article] [PubMed]
    [Google Scholar]
  7. Hu X, Du H, Ren C, Xu Y. Illuminating anaerobic microbial community and co-occurrence patterns across a quality gradient in Chinese liquor fermentation pit muds. Appl Environ Microbiol 2016; 82:2506–2515 [View Article] [PubMed]
    [Google Scholar]
  8. Wang X, Du H, Xu Y. Source tracking of prokaryotic communities in fermented grain of Chinese strong-flavor liquor. Int J Food Microbiol 2017; 244:27–35 [View Article] [PubMed]
    [Google Scholar]
  9. Xia H, Jin Y, Zhao D, Zhou R, Zheng J et al. Mining the factors driving the succession of microbial community in pit mud used for the production of Nongxiangxing baijiu. Lwt Food Sci Technol 2024; 195:115806 [View Article]
    [Google Scholar]
  10. Zou W, Zhao C, Luo H. Diversity and function of microbial community in Chinese strong-flavor Baijiu ecosystem: a review. Front Microbiol 2018; 9:671 [View Article] [PubMed]
    [Google Scholar]
  11. Wang H, Gu Y, Zhou W, Zhao D, Qiao Z et al. Adaptability of a caproate-producing bacterium contributes to its dominance in an anaerobic fermentation system. Appl Environ Microbiol 2021; 87:e0120321 [View Article] [PubMed]
    [Google Scholar]
  12. Gao J, Liu G, Li A, Liang C, Ren C et al. Domination of pit mud microbes in the formation of diverse flavour compounds during Chinese strong aroma-type Baijiu fermentation. Lwt Food Sci Technol 2021; 137:110442 [View Article]
    [Google Scholar]
  13. Pan F, Qiu S, Lv Y, Li D. Exploring the controllability of the Baijiu fermentation process with microbiota orientation. Food Res Int 2023; 173:113249 [View Article] [PubMed]
    [Google Scholar]
  14. Xu P-X, Chai L-J, Qiu T, Zhang X-J, Lu Z-M et al. Clostridium fermenticellae sp. nov., isolated from the mud in a fermentation cellar for the production of the Chinese liquor, Baijiu. Int J Syst Evol Microbiol 2019; 69:859–865 [View Article] [PubMed]
    [Google Scholar]
  15. Luo Q, Zheng J, Zhao D, Liu D. Clostridium aromativorans sp. nov., isolated from pit mud used for producing Wuliangye baijiu. Antonie van Leeuwenhoek 2023; 116:739–748 [View Article] [PubMed]
    [Google Scholar]
  16. Wang H, Gu Y, Zhao D, Qiao Z, Zheng J et al. Caproicibacterium lactatifermentans sp. nov., isolated from pit clay used for the production of Chinese strong aroma-type liquor. Int J Syst Evol Microbiol 2022; 72: [View Article] [PubMed]
    [Google Scholar]
  17. Liu Q, Zheng H, Wang H, Zhou W, Zhao D et al. Proteiniphilum propionicum sp. nov., a novel member of the phylum Bacteroidota isolated from pit clay used to produce Chinese liquor. Int J Syst Evol Microbiol 2022; 72: [View Article]
    [Google Scholar]
  18. Lu M, Zhou W, Ji F, Wu J, Nie Y et al. Profiling prokaryotic community in pit mud of Chinese strong-aroma type liquor by using oligotrophic culturing. Int J Food Microbiol 2021; 337:108951 [View Article] [PubMed]
    [Google Scholar]
  19. Hofstad T, Olsen I, Eribe ER, Falsen E, Collins MD et al. Dysgonomonas gen. nov. to accommodate Dysgonomonas gadei sp. nov., an organism isolated from a human gall bladder, and Dysgonomonas capnocytophagoides (formerly CDC group DF-3). Int J Syst Evol Microbiol 2000; 50 Pt 6:2189–2195 [View Article] [PubMed]
    [Google Scholar]
  20. Hahnke S, Langer T, Koeck DE, Klocke M. Description of Proteiniphilum saccharofermentans sp. nov., Petrimonas mucosa sp. nov. and Fermentimonas caenicola gen. nov., sp. nov., isolated from mesophilic laboratory-scale biogas reactors, and emended description of the genus Proteiniphilum. Int J Syst Evol Microbiol 2016; 66:1466–1475 [View Article]
    [Google Scholar]
  21. Grabowski A, Tindall BJ, Bardin V, Blanchet D, Jeanthon C. Petrimonas sulfuriphila gen. nov., sp. nov., a mesophilic fermentative bacterium isolated from a biodegraded oil reservoir. Int J Syst Evol Microbiol 2005; 55:1113–1121 [View Article] [PubMed]
    [Google Scholar]
  22. Chen S, Dong X. Proteiniphilum acetatigenes gen. nov., sp. nov., from a UASB reactor treating brewery wastewater. Int J Syst Evol Microbiol 2005; 55:2257–2261 [View Article] [PubMed]
    [Google Scholar]
  23. Liu L, Lv A-P, Li M-M, Ming Y-Z, Jiao J-Y et al. Seramator thermalis gen. nov., sp. nov., a novel cellulose- and xylan-degrading member of the family Dysgonamonadaceae isolated from a hot spring. Int J Syst Evol Microbiol 2020; 70:5717–5724 [View Article] [PubMed]
    [Google Scholar]
  24. Göker M, Oren A. Valid publication of names of two domains and seven kingdoms of prokaryotes. Int J Syst Evol Microbiol 2024; 74: [View Article]
    [Google Scholar]
  25. Oren A, Garrity GM. Valid publication of the names of forty-two phyla of prokaryotes. Int J Syst Evol Microbiol 2021; 71: [View Article]
    [Google Scholar]
  26. Ormerod KL, Wood DLA, Lachner N, Gellatly SL, Daly JN et al. Genomic characterization of the uncultured Bacteroidales family S24-7 inhabiting the guts of homeothermic animals. Microbiome 2016; 4:36 [View Article] [PubMed]
    [Google Scholar]
  27. Koblitz J, Halama P, Spring S, Thiel V, Baschien C et al. MediaDive: the expert-curated cultivation media database. Nucleic Acids Res 2023; 51:D1531–D1538 [View Article] [PubMed]
    [Google Scholar]
  28. Frank JA, Reich CI, Sharma S, Weisbaum JS, Wilson BA et al. Critical evaluation of two primers commonly used for amplification of bacterial 16S rRNA genes. Appl Environ Microbiol 2008; 74:2461–2470 [View Article] [PubMed]
    [Google Scholar]
  29. 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]
  30. Felsenstein J. Confidence limits on phylogenies: an approach using the bootstrap. Evolution 1985; 39:783–791 [View Article] [PubMed]
    [Google Scholar]
  31. Saitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 1987; 4:406–425 [View Article] [PubMed]
    [Google Scholar]
  32. Yarza P, Yilmaz P, Pruesse E, Glöckner FO, Ludwig W et al. Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences. Nat Rev Microbiol 2014; 12:635–645 [View Article] [PubMed]
    [Google Scholar]
  33. Kim M, Oh HS, Park SC, Chun J. Towards a taxonomic coherence between average nucleotide identity and 16S rRNA gene sequence similarity for species demarcation of prokaryotes. Int J Syst Evol Microbiol 2014; 64:346–351 [View Article] [PubMed]
    [Google Scholar]
  34. Wick RR, Judd LM, Gorrie CL, Holt KE. Unicycler: resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput Biol 2017; 13:e1005595 [View Article] [PubMed]
    [Google Scholar]
  35. 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]
  36. Krawczyk PS, Lipinski L, Dziembowski A. PlasFlow: predicting plasmid sequences in metagenomic data using genome signatures. Nucleic Acids Res 2018; 46:e35-e35 [View Article] [PubMed]
    [Google Scholar]
  37. 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]
  38. Haft DH, DiCuccio M, Badretdin A, Brover V, Chetvernin V et al. RefSeq: an update on prokaryotic genome annotation and curation. Nucleic Acids Res 2018; 46:D851–D860 [View Article] [PubMed]
    [Google Scholar]
  39. Kanehisa M, Furumichi M, Sato Y, Kawashima M, Ishiguro-Watanabe M. KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Res 2023; 51:D587–D592 [View Article] [PubMed]
    [Google Scholar]
  40. Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol 2016; 428:726–731 [View Article] [PubMed]
    [Google Scholar]
  41. Cantalapiedra CP, Hernández-Plaza A, Letunic I, Bork P, Huerta-Cepas J. eggNOG-mapper v2: functional annotation, orthology assignments, and domain prediction at the metagenomic scale. Mol Biol Evol 2021; 38:5825–5829 [View Article] [PubMed]
    [Google Scholar]
  42. Zheng J, Ge Q, Yan Y, Zhang X, Huang L et al. dbCAN3: automated carbohydrate-active enzyme and substrate annotation. Nucleic Acids Res 2023; 51:W115–W121 [View Article] [PubMed]
    [Google Scholar]
  43. Blin K, Shaw S, Augustijn HE, Reitz ZL, Biermann F et al. antiSMASH 7.0: new and improved predictions for detection, regulation, chemical structures and visualisation. Nucleic Acids Res 2023; 51:W46–W50 [View Article] [PubMed]
    [Google Scholar]
  44. Meier-Kolthoff JP, Carbasse JS, Peinado-Olarte RL, Göker M. TYGS and LPSN: a database tandem for fast and reliable genome-based classification and nomenclature of prokaryotes. Nucleic Acids Res 2022; 50:D801–D807 [View Article] [PubMed]
    [Google Scholar]
  45. Yoon SH, Ha SM, 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]
  46. 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]
  47. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article] [PubMed]
    [Google Scholar]
  48. Parks DH, Rinke C, Chuvochina M, Chaumeil P-A, Woodcroft BJ et al. Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life. Nat Microbiol 2017; 2:1533–1542 [View Article] [PubMed]
    [Google Scholar]
  49. Zhang D-F, He W, Shao Z, Ahmed I, Zhang Y et al. EasyCGTree: a pipeline for prokaryotic phylogenomic analysis based on core gene sets. BMC Bioinf 2023; 24:390 [View Article] [PubMed]
    [Google Scholar]
  50. van der Maarel MJEC, van der Veen B, Uitdehaag JCM, Leemhuis H, Dijkhuizen L. Properties and applications of starch-converting enzymes of the alpha-amylase family. J Biotechnol 2002; 94:137–155 [View Article] [PubMed]
    [Google Scholar]
  51. Zdouc Mitja M, Blin K, Louwen Nico LL, Navarro J, Loureiro C et al. MIBiG 4.0: advancing biosynthetic gene cluster curation through global collaboration. Nucleic Acids Res 2024; 53:D678–D690
    [Google Scholar]
  52. Richter M, Rosselló-Móra R. Shifting the genomic gold standard for the prokaryotic species definition. Proc Natl Acad Sci USA 2009; 106:19126–19131 [View Article] [PubMed]
    [Google Scholar]
  53. Halebian S, Harris B, Finegold SM, Rolfe RD. Rapid method that aids in distinguishing Gram-positive from Gram-negative anaerobic bacteria. J Clin Microbiol 1981; 13:444–448 [View Article] [PubMed]
    [Google Scholar]
  54. Minnikin DE, O’Donnell AG, Goodfellow M, Alderson G, Athalye M et al. An integrated procedure for the extraction of bacterial isoprenoid quinones and polar lipids. J Microbiol Methods 1984; 2:233–241 [View Article]
    [Google Scholar]
  55. Collins MD, Jones D. Lipids in the classification and identification of coryneform bacteria containing peptidoglycans based on 2, 4-diaminobutyric acid. J Appl Microbiol 1980; 48:459–470 [View Article]
    [Google Scholar]
  56. Sasser M. Identification of bacteria by gas chromatography of cellular fatty acids. USFCC Newsl 1990; 20:1–6
    [Google Scholar]
/content/journal/ijsem/10.1099/ijsem.0.006702
Loading
/content/journal/ijsem/10.1099/ijsem.0.006702
Loading

Data & Media loading...

Supplements

Supplementary material 1

Supplementary material 2

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