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Microbiology spectrum2023; 11(5); e0504822; doi: 10.1128/spectrum.05048-22

Kinetic, genomic, and physiological analysis reveals diversity in the ecological adaptation and metabolic potential of Brachybacterium equifaecis sp. nov. isolated from horse feces.

Abstract: Brachybacterium species have been identified in various ecological niches and belong to the family within the phylum . In this study, we isolated a novel JHP9 strain from horse feces and compared its kinetic, biochemical, and genomic features with those of other strains. Moreover, comparative genomic analysis using publicly available genomes was performed to determine the properties involved in their ecological adaptation and metabolic potential. Novel species delineation was determined phylogenetically through 16S rRNA gene similarity (up to 97.9%), average nucleotide identity (79.5-82.5%), average amino acid identity (66.7-75.8%), and DNA-DNA hybridization (23.7-27.9) using closely related strains. This study also presents the first report of the kinetic properties of species. Most of the strains displayed high oxygen ( =1.6-24.2 µM) and glucose ( =0.73-1.22 µM) affinities, which may manifest niche adaptations. Various carbohydrate metabolisms under aerobic and anaerobic conditions, antibiotic resistance, mobile genetic elements, carbohydrate-active enzymes, lactic acid production, and the clustered regularly interspaced short palindromic repeats-Cas and bacteriophage exclusion systems were observed in the genotypic and/or phenotypic properties of species, suggesting their genome flexibility, defense mechanisms, and adaptability. Our study contributes to the knowledge of the kinetic, physiological, and genomic properties of species, including the novel JHP9 strain, which advocates for their tolerant and thriving nature in various environments, leading to their ecological adaptation. IMPORTANCE Basic physiological and genomic properties of most of the isolates have been studied; however, the ability of this bacterium to adapt to diverse environments, which may demonstrate its role in niche differentiation, is to be identified yet. Therefore, here, we explored cellular kinetics, metabolic diversity, and ecological adaptation/defensive properties of the novel strain through physiological and comparative genomic analysis. In addition, we presented the first report examining kinetics, indicating that all strains of , including the novel one, have high oxygen and glucose affinity. Furthermore, the comparative genomic analysis also revealed that the novel bacterium contains versatile genomic properties, which provide the novel bacterium with significant competitive advantages. Thus, in-depth genotypic and phenotypic analysis with kinetic properties at the species level of this genus is beneficial in clarifying its differential characteristics, conferring the ability to inhabit diverse ecological niches.
Publication Date: 2023-09-14 PubMed ID: 37707449PubMed Central: PMC10581053DOI: 10.1128/spectrum.05048-22Google Scholar: Lookup
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  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research article deals with the identification and study of a new strain of bacterium, Brachybacterium equifaecis sp. nov., found in horse feces, understanding its ecological adaptations, genetic features, and metabolic potential. The study also provides the debut reporting of kinetic properties of Brachybacterium species, with insights into their adaptability and defensive mechanisms.

Introduction

  • The research focuses on a newly isolated strain of Brachybacterium (JHP9) found in horse feces. Brachybacterium species have been found in several ecological niches but their adaptability to inhabit different environments is less explored.
  • The objective is to understand the bacterium’s kinetic, biochemical, genomic characteristics, and compare them with other Brachybacterium strains. Also, the ambition is to discover properties that help in their eco-adaptation and metabolic potential via genomic analysis.

Methodology

  • The study distinguishes the novel species through 16S rRNA gene similarity and other genetic benchmarks such as average nucleotide identity, average amino acid identity, and DNA-DNA hybridization with related strains.
  • A comparative genomic examination involving publicly available Brachybacterium genomes was carried out to understand their ecological adaptation and metabolic potential.

Findings

  • The novel species JHP9 and others revealed high oxygen and glucose affinities, indicating potential niche adaptations.
  • The researchers identified various properties through genotypic and/or phenotypic analysis that provided insights into their adaptability. These included different carbohydrate metabolic pathways under both aerobic and anaerobic conditions, resistance to antibiotics, presence of mobile genetic elements, and carbohydrate-active enzymes. Plus, attributes such as lactic acid production and defense mechanisms like the Clustered Regularly Interspaced Short Palindromic Repeats-Cas and bacteriophage exclusion systems were also noted.
  • These findings suggest significant genome flexibility in Brachybacterium species that equip them with defense mechanisms and adaptability, supporting their survival and growth in diverse environments.

Conclusion

  • The research enhances understanding about novel Brachybacterium equifaecis sp. nov. strain (JHP9) and the kinetic, physiological, and genomic properties of Brachybacterium species in general.
  • The newly discovered strain, along with the others, exhibit high affinities towards oxygen and glucose potentially aiding their environmental adaptation. Diverse genomic properties further provide these bacteria with competitive advantages.
  • Comprehensive genotypic and phenotypic analysis, along with kinetic properties at the species level, support the differential characteristics of Brachybacterium species that allow them to inhabit varied eco niches. Hence, this study provides a solid foundation for further ecological and microbiological analysis.

Cite This Article

APA
Farooq A, Lee M, Han S, Jung GY, Kim SJ, Jung MY. (2023). Kinetic, genomic, and physiological analysis reveals diversity in the ecological adaptation and metabolic potential of Brachybacterium equifaecis sp. nov. isolated from horse feces. Microbiol Spectr, 11(5), e0504822. https://doi.org/10.1128/spectrum.05048-22

Publication

ISSN: 2165-0497
NlmUniqueID: 101634614
Country: United States
Language: English
Volume: 11
Issue: 5
Pages: e0504822
PII: e05048-22

Researcher Affiliations

Farooq, Adeel
  • Research Institute for Basic Sciences (RIBS), Jeju National University , Jeju, South Korea.
Lee, Myunglip
  • Department of Marine Life Science, Jeju National University , Jeju, South Korea.
Han, Saem
  • Interdisciplinary Graduate Programme in Advance Convergence Technology and Science, Jeju National University , Jeju, South Korea.
Jung, Gi-Yong
  • Mineral Resources Research Division, Korea Institute of Geoscience and Mineral Resources , Daejeon, South Korea.
  • Department of Biological Sciences and Biotechnology, Chungbuk National University , Cheongju, South Korea.
Kim, So-Jeong
  • Mineral Resources Research Division, Korea Institute of Geoscience and Mineral Resources , Daejeon, South Korea.
Jung, Man-Young
  • Interdisciplinary Graduate Programme in Advance Convergence Technology and Science, Jeju National University , Jeju, South Korea.
  • Department of Science Education, Jeju National University , Jeju, South Korea.
  • Jeju Microbiome Center, Jeju National University , Jeju, South Korea.

Conflict of Interest Statement

The authors declare no conflict of interest.

References

This article includes 97 references
  1. Louca S, Mazel F, Doebeli M, Parfrey LW. A census-based estimate of earth’s bacterial and archaeal diversity. PLoS Biol 2019 17:e3000106.
  2. Kauter A, Epping L, Semmler T, Antao E-M, Kannapin D, Stoeckle SD, Gehlen H, Lübke-Becker A, Günther S, Wieler LH, Walther B. The gut microbiome of horses: current research on equine enteral microbiota and future perspectives. Anim Microbiome 2019 1:14.
    doi: 10.1186/s42523-019-0013-3pmc: PMC7807895pubmed: 33499951google scholar: lookup
  3. Wunderlich G, Bull M, Ross T, Rose M, Chapman B. Understanding the microbial fibre degrading communities & processes in the equine gut. Anim Microbiome 2023 5:3.
    doi: 10.1186/s42523-022-00224-6pmc: PMC9837927pubmed: 36635784google scholar: lookup
  4. Liu Y, Zhai L, Yao S, Cao Y, Cao Y, Zhang X, Su J, Ge Y, Zhao R, Cheng C. Brachybacterium hainanense sp. nov., isolated from noni (Morinda citrifolia L.) branch. Int J Syst Evol Microbiol 2015 65:4196–4201.
    doi: 10.1099/ijsem.0.000559pubmed: 26311250google scholar: lookup
  5. Chang DH, Rhee MS, Kim BC. Dermabacter vaginalis sp. nov., isolated from human vaginal fluid. Int J Syst Evol Microbiol 2016 66:1881–1886.
    doi: 10.1099/ijsem.0.000960pubmed: 26867728google scholar: lookup
  6. Park YK, Lee KM, Lee WK, Cho MJ, Lee HS, Cho YG, Lee YC, Lee WK, Seong WK, Hwang KJ. Dermabacter jinjuensis sp. nov., a novel species of the genus Dermabacter isolated from a clinical specimen. Int J Syst Evol Microbiol 2016 66:2573–2577.
    doi: 10.1099/ijsem.0.001092pubmed: 27088668google scholar: lookup
  7. Tak EJ, Kim PS, Hyun D-W, Kim HS, Lee J-Y, Kang W, Sung H, Shin N-R, Kim M-S, Whon TW, Bae J-W. Phenotypic and genomic properties of Brachybacterium vulturis sp. nov. and Brachybacterium avium sp. nov.. Front. Microbiol 2018 9.
    doi: 10.3389/fmicb.2018.01809pmc: PMC6090031pubmed: 30131788google scholar: lookup
  8. Mekhalif F, Tidjani Alou M, Zgheib R, Lo CI, Fournier PE, Raoult D, Lagier JC. Brachybacterium massiliense sp. nov., a new bacterium isolated from stool from a healthy senegalese child. New Microbes New Infect 2019 31:100588.
    doi: 10.1016/j.nmni.2019.100588pmc: PMC6710231pubmed: 31463068google scholar: lookup
  9. Tamai K, Akashi Y, Yoshimoto Y, Yaguchi Y, Takeuchi Y, Shiigai M, Igarashi J, Hirose Y, Suzuki H, Ohkusu K. First case of a bloodstream infection caused by the genus Brachybacterium. J Infect Chemother 2018 24:998–1003.
    doi: 10.1016/j.jiac.2018.06.005pubmed: 30007866google scholar: lookup
  10. van Elsas JD, Semenov AV, Costa R, Trevors JT. Survival of Escherichia coli in the environment: fundamental and public health aspects. ISME J 2011 5:173–183.
    doi: 10.1038/ismej.2010.80pmc: PMC3105702pubmed: 20574458google scholar: lookup
  11. Hibbing ME, Fuqua C, Parsek MR, Peterson SB. Bacterial competition: surviving and thriving in the microbial jungle. Nat Rev Microbiol 2010 8:15–25.
    doi: 10.1038/nrmicro2259pmc: PMC2879262pubmed: 19946288google scholar: lookup
  12. Chou JH, Lin KY, Lin MC, Sheu SY, Wei YH, Arun AB, Young CC, Chen WM. Brachybacterium phenoliresistens sp. nov., isolated from oil-contaminated coastal sand. Int J Syst Evol Microbiol 2007 57:2674–2679.
    doi: 10.1099/ijs.0.65019-0pubmed: 17978239google scholar: lookup
  13. Hlaing PPT, Junqueira ACM, Uchida A, Purbojati RW, Houghton JNI, Chénard C, Wong A, Clare ME, Kushwaha KK, Putra A, Kee C, Gaultier NE, Premkrishnan BNV, Heinle CE, Lim SBY, Vettah VK, Drautz-Moses DI, Schuster SC. Complete genome sequence of Brachybacterium sp. Strain SGAir0954, isolated from Singapore air. Microbiol Resour Announc 2019 8:e00619-19.
    doi: 10.1128/MRA.00619-19pmc: PMC6687925pubmed: 31395638google scholar: lookup
  14. Ming H, Cheng LJ, Yi BF, Xia TT, Niu MM, Zhao ZY, Liu BB, Nie GX, Cui CX. Brachybacterium subflavum sp. nov., a novel actinobacterium isolated from the foregut of grass carp. Int J Syst Evol Microbiol 2021 71.
    doi: 10.1099/ijsem.0.004839pubmed: 34170217google scholar: lookup
  15. Jung M-Y, Sedlacek CJ, Kits KD, Mueller AJ, Rhee S-K, Hink L, Nicol GW, Bayer B, Lehtovirta-Morley L, Wright C, de la Torre JR, Herbold CW, Pjevac P, Daims H, Wagner M. Ammonia-oxidizing archaea possess a wide range of cellular ammonia affinities. ISME J 2022 16:272–283.
    doi: 10.1038/s41396-021-01064-zpmc: PMC8692354pubmed: 34316016google scholar: lookup
  16. Ciufo S, Kannan S, Sharma S, Badretdin A, Clark K, Turner S, Brover S, Schoch CL, Kimchi A, DiCuccio M. Using average nucleotide identity to improve taxonomic assignments in prokaryotic genomes at the NCBI. Int J Syst Evol Microbiol 2018 68:2386–2392.
    pmc: PMC6978984pubmed: 29792589
  17. Meier-Kolthoff JP, Auch AF, Klenk HP, Göker M. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinform 2013 14:60.
    doi: 10.1186/1471-2105-14-60pmc: PMC3665452pubmed: 23432962google scholar: lookup
  18. Konstantinidis KT, Tiedje JM. Towards a genome-based taxonomy for prokaryotes. J Bacteriol 2005 187:6258–6264.
  19. Medlar AJ, Törönen P, Holm L. AAI-profiler: fast proteome-wide exploratory analysis reveals taxonomic identity, misclassification and contamination. Nucleic Acids Res 2018 46:W479–W485.
    doi: 10.1093/nar/gky359pmc: PMC6030964pubmed: 29762724google scholar: lookup
  20. Gvozdyak OR, Nogina TM, Schumann P. Taxonomic study of the genus Brachybacterium: Brachybacterium nesterenkovii sp. nov.. Int J Syst Bacteriol 1992 42:74–78.
    doi: 10.1099/00207713-42-1-74pubmed: 1736971google scholar: lookup
  21. Leyn SA, Maezato Y, Romine MF, Rodionov DA. Genomic reconstruction of carbohydrate utilization capacities in microbial-mat derived consortia. Front Microbiol 2017 8:1304.
    doi: 10.3389/fmicb.2017.01304pmc: PMC5507952pubmed: 28751880google scholar: lookup
  22. Stolper DA, Revsbech NP, Canfield DE. Aerobic growth at nanomolar oxygen concentrations. Proc Natl Acad Sci U S A 2010 107:18755–18760.
    doi: 10.1073/pnas.1013435107pmc: PMC2973883pubmed: 20974919google scholar: lookup
  23. Bodelier PLE, Laanbroek HJ. Oxygen uptake kinetics of Pseudomonas chlororaphis grown in glucose- or glutamate-limited continuous cultures. Arch Microbiol 1997 167:392–395.
    doi: 10.1007/s002030050460google scholar: lookup
  24. Martens-Habbena W, Berube PM, Urakawa H, de la Torre JR, Stahl DA. Ammonia oxidation kinetics determine niche separation of nitrifying archaea and bacteria. Nature 2009 461:976–979.
    doi: 10.1038/nature08465pubmed: 19794413google scholar: lookup
  25. Cox RP, Marling N. High-affinity oxygen uptake by Bifidobacterium bifidum. Antonie Van Leeuwenhoek 1992 62:291–297.
    doi: 10.1007/BF00572597pubmed: 1285646google scholar: lookup
  26. Hardin G. The competitive exclusion principle. Science 1960 131:1292–1297.
    doi: 10.1126/science.131.3409.1292pubmed: 14399717google scholar: lookup
  27. Abbott DW, van Bueren AL. Using structure to inform carbohydrate binding module function. Curr Opin Struct Biol 2014 28:32–40.
    doi: 10.1016/j.sbi.2014.07.004pubmed: 25108190google scholar: lookup
  28. Munir RI, Schellenberg J, Henrissat B, Verbeke TJ, Sparling R, Levin DB. Comparative analysis of carbohydrate active enzymes in clostridium termitidis CT1112 reveals complex carbohydrate degradation ability. PLoS One 2014 9:e104260.
  29. Yao T, Chen M-H, Lindemann SR. Structurally complex carbohydrates maintain diversity in gut-derived microbial consortia under high dilution pressure. FEMS Microbiol Ecol 2020 96:fiaa158.
    doi: 10.1093/femsec/fiaa158pubmed: 32815998google scholar: lookup
  30. Singhvi M, Zendo T, Sonomoto K. Free lactic acid production under acidic conditions by lactic acid bacteria strains: challenges and future prospects. Appl Microbiol Biotechnol 2018 102:5911–5924.
    doi: 10.1007/s00253-018-9092-4pubmed: 29804138google scholar: lookup
  31. George F, Daniel C, Thomas M, Singer E, Guilbaud A, Tessier FJ, Revol-Junelles AM, Borges F, Foligné B. Occurrence and dynamism of lactic acid bacteria in distinct ecological niches: a multifaceted functional health perspective. Front Microbiol 2018 9:2899.
    doi: 10.3389/fmicb.2018.02899pmc: PMC6277688pubmed: 30538693google scholar: lookup
  32. Abedi E, Hashemi SMB. Lactic acid production–producing microorganisms and substrates sources-state of art. Heliyon 2020 6:e04974.
  33. Montero-Zamora J, Fernández-Fernández S, Redondo-Solano M, Mazón-Villegas B, Mora-Villalobos JA, Barboza N. Assessment of different lactic acid bacteria isolated from agro-industrial residues: first report of the potential role of Weissella soli for lactic acid production from milk whey. Appl Microbiol 2022 2:626–635.
  34. Liu Y, Xie QY, Shi W, Li L, An JY, Zhao YM, Hong K. Brachybacterium huguangmaarense sp. nov., isolated from lake sediment. Int J Syst Evol Microbiol 2014 64:1673–1678.
    doi: 10.1099/ijs.0.052464-0pubmed: 24532648google scholar: lookup
  35. Esposti MD. On the evolution of cytochrome oxidases consuming oxygen. Biochim Biophys Acta Bioenerg 2020 1861:148304.
    doi: 10.1016/j.bbabio.2020.148304pubmed: 32890468google scholar: lookup
  36. Rice CW, Hempfling WP. Oxygen-limited continuous culture and respiratory energy conservation in Escherichia coli. J Bacteriol 1978 134:115–124.
    doi: 10.1128/jb.134.1.115-124.1978pmc: PMC222225pubmed: 25879google scholar: lookup
  37. D’Mello R, Hill S, Poole RK. The oxygen affinity of cytochrome bo' in Escherichia coli determined by the deoxygenation of oxyleghemoglobin and oxymyoglobin: km values for oxygen are in the submicromolar range. J Bacteriol 1995 177:867–870.
    doi: 10.1128/jb.177.3.867-870.1995pmc: PMC176676pubmed: 7836332google scholar: lookup
  38. Jahreis K, Pimentel-Schmitt EF, Brückner R, Titgemeyer F. Ins and outs of glucose transport systems in eubacteria. FEMS Microbiol Rev 2008 32:891–907.
  39. Button DK. Biochemical basis for whole-cell uptake kinetics: specific affinity, oligotrophic capacity, and the meaning of the michaelis constant. Appl Environ Microbiol 1991 57:2033–2038.
  40. Ishida Y, Imai I, Miyagaki T, Kadota H. Growth and uptake kinetics of a facultatively oligotrophic bacterium at low nutrient concentrations. Microb Ecol 1982 8:23–32.
    doi: 10.1007/BF02011458pubmed: 24225695google scholar: lookup
  41. Martens-Habbena W, Stahl DA. Nitrogen metabolism and kinetics of ammonia-oxidizing archaea. Methods Enzymol 2011 496:465–487.
  42. Corona F, Martinez JL. Phenotypic resistance to antibiotics. Antibiotics (Basel) 2013 2:237–255.
    doi: 10.3390/antibiotics2020237pmc: PMC4790337pubmed: 27029301google scholar: lookup
  43. Depardieu F, Podglajen I, Leclercq R, Collatz E, Courvalin P. Modes and modulations of antibiotic resistance gene expression. Clin Microbiol Rev 2007 20:79–114.
    doi: 10.1128/CMR.00015-06pmc: PMC1797629pubmed: 17223624google scholar: lookup
  44. Hughes D, Andersson DI. Environmental and genetic modulation of the phenotypic expression of antibiotic resistance. FEMS Microbiol Rev 2017 41:374–391.
    doi: 10.1093/femsre/fux004pmc: PMC5435765pubmed: 28333270google scholar: lookup
  45. Murata K, Ozawa K, Kawakami H, Mochizuki K, Ohkusu K. Brachybacterium paraconglomeratum endophthalmitis postcataract operation. Case Rep Ophthalmol Med 2020 2020:1513069.
    doi: 10.1155/2020/1513069pmc: PMC7091523pubmed: 32231828google scholar: lookup
  46. Tian M, He X, Feng Y, Wang W, Chen H, Gong M, Liu D, Clarke JL, van Eerde A. Pollution by antibiotics and antimicrobial resistance in livestock and poultry manure in China, and countermeasures. Antibiotics (Basel) 2021 10:539.
    doi: 10.3390/antibiotics10050539pmc: PMC8148549pubmed: 34066587google scholar: lookup
  47. Goldfarb T, Sberro H, Weinstock E, Cohen O, Doron S, Charpak-Amikam Y, Afik S, Ofir G, Sorek R. BREX is a novel phage resistance system widespread in microbial genomes. EMBO J 2015 34:169–183.
    doi: 10.15252/embj.201489455pmc: PMC4337064pubmed: 25452498google scholar: lookup
  48. Hille F, Charpentier E. CRISPR-Cas: biology, mechanisms and relevance. Philos Trans R Soc Lond B Biol Sci 2016 371:20150496.
    doi: 10.1098/rstb.2015.0496pmc: PMC5052741pubmed: 27672148google scholar: lookup
  49. Mat Razali N, Cheah BH, Nadarajah K. Transposable elements adaptive role in genome plasticity, pathogenicity and evolution in fungal phytopathogens. Int J Mol Sci 2019 20:3597.
    doi: 10.3390/ijms20143597pmc: PMC6679389pubmed: 31340492google scholar: lookup
  50. Fan C, Wu Y-H, Decker CM, Rohani R, Gesell Salazar M, Ye H, Cui Z, Schmidt F, Huang WE. Defensive function of transposable elements in bacteria. ACS Synth Biol 2019 8:2141–2151.
    doi: 10.1021/acssynbio.9b00218pubmed: 31375026google scholar: lookup
  51. Farooq A, Kim J, Raza S, Jang J, Han D, Sadowsky MJ, Unno T. A hybrid DNA sequencing approach is needed to properly link genotype to phenotype in multi-drug resistant bacteria. Environ Pollut 2021 289:117856.
    doi: 10.1016/j.envpol.2021.117856pubmed: 34330011google scholar: lookup
  52. Borisov VB, Gennis RB, Hemp J, Verkhovsky MI. The cytochrome bd respiratory oxygen reductases. Biochim Biophys Acta Bioenerg 2011 1807:1398–1413.
  53. D’mello R, Hill S, Poole RK. The cytochrome bd quinol oxidase in Escherichia coli has an extremely high oxygen affinity and two oxygen-binding haems: implications for regulation of activity in vivo by oxygen inhibition. Microbiology (Reading) 1996 142 (Pt 4):755–763.
    doi: 10.1099/00221287-142-4-755pubmed: 8936304google scholar: lookup
  54. Bottacini F, Milani C, Turroni F, Sánchez B, Foroni E, Duranti S, Serafini F, Viappiani A, Strati F, Ferrarini A, Delledonne M, Henrissat B, Coutinho P, Fitzgerald GF, Margolles A, van Sinderen D, Ventura M. Bifidobacterium asteroides PRL2011 genome analysis reveals clues for colonization of the insect gut. PLoS One 2012 7:e44229.
  55. Gong X, Garcia-Robledo E, Schramm A, Revsbech NP. Respiratory kinetics of marine bacteria exposed to decreasing oxygen concentrations. Appl Environ Microbiol 2015 82:1412–1422.
    doi: 10.1128/AEM.03669-15pmc: PMC4771329pubmed: 26682857google scholar: lookup
  56. Passalacqua KD, Charbonneau M-E, O’Riordan MXD. Bacterial metabolism shapes the host-pathogen interface. Microbiol Spectr 2016 4.
  57. Woodcock DJ, Krusche P, Strachan NJC, Forbes KJ, Cohan FM, Méric G, Sheppard SK. Genomic plasticity and rapid host switching can promote the evolution of generalism: a case study in the zoonotic pathogen Campylobacter. Sci Rep 2017 7:9650.
    doi: 10.1038/s41598-017-09483-9pmc: PMC5575054pubmed: 28851932google scholar: lookup
  58. Hassan L. Emerging Zoonoses in domesticated livestock of Southeast Asia. 2014 2nd ed. Elsvier, Amsterdam, AM.
  59. Weisburg WG, Barns SM, Pelletier DA, Lane DJ. 16S ribosomal DNA amplification for phylogenetic study. J Bacteriol 1991 173:697–703.
    doi: 10.1128/jb.173.2.697-703.1991pmc: PMC207061pubmed: 1987160google scholar: lookup
  60. Alzohairy A. BioEdit: an important software for molecular biology. GERF bull biosci 2011 2:60–61.
  61. Pruesse E, Quast C, Knittel K, Fuchs BM, Ludwig W, Peplies J, Glöckner FO. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res 2007 35:7188–7196.
    doi: 10.1093/nar/gkm864pmc: PMC2175337pubmed: 17947321google scholar: lookup
  62. Tamura K, Stecher G, Kumar S. MEGA11: molecular evolutionary genetics analysis version 11. Mol Biol Evol 2021 38:3022–3027.
    doi: 10.1093/molbev/msab120pmc: PMC8233496pubmed: 33892491google scholar: lookup
  63. 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.
    doi: 10.1007/BF01731581pubmed: 7463489google scholar: lookup
  64. Taylor WI, Achanzar D. Catalase test as an aid to the identification of enterobacteriaceae. Appl Microbiol 1972 24:58–61.
    doi: 10.1128/am.24.1.58-61.1972pmc: PMC380547pubmed: 4560474google scholar: lookup
  65. Tarrand JJ, Gröschel DH. Rapid, modified oxidase test for oxidase-variable bacterial isolates. J Clin Microbiol 1982 16:772–774.
    doi: 10.1128/jcm.16.4.772-774.1982pmc: PMC272470pubmed: 7153330google scholar: lookup
  66. Hanson A. Oxidative-Fermentative test protocol. ASM press, Washington, DC 2008.
  67. Gordon RE, Smith MM. Rapidly growing, acid fast bacteria. I. species' descriptions of Mycobacterium phlei lehmann and neumann and Mycobacterium smegmatis (trevisan) lehmann and neumann. J Bacteriol 1953 66:41–48.
    doi: 10.1128/jb.66.1.41-48.1953pmc: PMC357089pubmed: 13069464google scholar: lookup
  68. Holding A, Collee J. Chapter I routine biochemical tests, p 1–32. In Methods in microbiology. Elsevier, Amsterdam, AM 1971.
  69. de Fátima Silva Lopes M, Ribeiro T, Abrantes M, Figueiredo Marques JJ, Tenreiro R, Crespo MTB. Antimicrobial resistance profiles of dairy and clinical isolates and type strains of enterococci. Int J Food Microbiol 2005 103:191–198.
  70. Cummins CS, Harris H. The chemical composition of the cell wall in some gram-positive bacteria and its possible value as a taxonomic character. J Gen Microbiol 1956 14:583–600.
    doi: 10.1099/00221287-14-3-583pubmed: 13346020google scholar: lookup
  71. Sasser M. Identification of bacteria by gas chromatography of cellular fatty acids, In MIDI technical NOTE 101. MIDI inc, Newark, DE 1990.
  72. Schleifer K, Seidl P, Goodfellow M, Minnikin D. Chemical methods in bacterial systematics. The Society for Applied Bacteriology, London 1985.
  73. Hiraishi A, Ueda Y, Ishihara J, Mori T. Comparative lipoquinone analysis of influent sewage and activated sludge by high-performance liquid chromatography and photodiode array detection. J Gen Appl Microbiol 1996 42:457–469.
    doi: 10.2323/jgam.42.457google scholar: lookup
  74. Collins MD, Jones D. Distribution of isoprenoid quinone structural types in bacteria and their taxonomic implication. Microbiol Rev 1981 45:316–354.
    doi: 10.1128/mr.45.2.316-354.1981pmc: PMC281511pubmed: 7022156google scholar: lookup
  75. Lee M, Farooq A, Jung M-Y, Kim S-J. Draft genome sequence of Brachybacterium sp. JHP9 isolated from horse feces in Jeju Island. Korean J Microbiol 2022 58:102–104.
  76. Chen S, Zhou Y, Chen Y, Gu J. Fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 2018 34:i884–i890.
  77. Prjibelski A, Antipov D, Meleshko D, Lapidus A, Korobeynikov A. Using spades de novo assembler. Curr Protoc Bioinformatics 2020 70:e102.
    doi: 10.1002/cpbi.102pubmed: 32559359google scholar: lookup
  78. Simão FA, Waterhouse RM, Ioannidis P, Kriventseva EV, Zdobnov EM. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 2015 31:3210–3212.
    doi: 10.1093/bioinformatics/btv351pubmed: 26059717google scholar: lookup
  79. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014 30:2068–2069.
    doi: 10.1093/bioinformatics/btu153pubmed: 24642063google scholar: lookup
  80. Mistry J, Chuguransky S, Williams L, Qureshi M, Salazar GA, Sonnhammer ELL, Tosatto SCE, Paladin L, Raj S, Richardson LJ, Finn RD, Bateman A. Pfam: the protein families database in 2021. Nucleic Acids Res 2021 49:D412–D419.
    doi: 10.1093/nar/gkaa913pmc: PMC7779014pubmed: 33125078google scholar: lookup
  81. Park BH, Karpinets TV, Syed MH, Leuze MR, Uberbacher EC. CAZymes analysis toolkit (CAT): web service for searching and analyzing carbohydrate-active enzymes in a newly sequenced organism using CAZy database. Glycobiology 2010 20:1574–1584.
    doi: 10.1093/glycob/cwq106pubmed: 20696711google scholar: lookup
  82. Yin Y, Mao X, Yang J, Chen X, Mao F, Xu Y. dbCAN: a web resource for automated carbohydrate-active enzyme annotation. Nucleic Acids Res 2012 40:W445–W451.
    doi: 10.1093/nar/gks479pmc: PMC3394287pubmed: 22645317google scholar: lookup
  83. Blin K, Shaw S, Kloosterman AM, Charlop-Powers Z, van Wezel GP, Medema MH, Weber T. antiSMASH 6.0: improving cluster detection and comparison capabilities. Nucleic Acids Res 2021 49:W29–W35.
    doi: 10.1093/nar/gkab335pmc: PMC8262755pubmed: 33978755google scholar: lookup
  84. Feldgarden M, Brover V, Haft DH, Prasad AB, Slotta DJ, Tolstoy I, Tyson GH, Zhao S, Hsu C-H, McDermott PF, Tadesse DA, Morales C, Simmons M, Tillman G, Wasilenko J, Folster JP, Klimke W. Validating the AMRFinder tool and resistance gene database by using antimicrobial resistance genotype-phenotype correlations in a collection of isolates. Antimicrob Agents Chemother 2019 63:e00483-19.
    doi: 10.1128/AAC.00483-19pmc: PMC6811410pubmed: 31427293google scholar: lookup
  85. Chen L, Yang J, Yu J, Yao Z, Sun L, Shen Y, Jin Q. VFDB: a reference database for bacterial virulence factors. Nucleic Acids Res 2005 33:D325–D328.
    doi: 10.1093/nar/gki008pmc: PMC539962pubmed: 15608208google scholar: lookup
  86. Xie Z, Tang H, Hancock J. ISEScan: automated identification of insertion sequence elements in prokaryotic genomes. Bioinformatics 2017 33:3340–3347.
    doi: 10.1093/bioinformatics/btx433pubmed: 29077810google scholar: lookup
  87. Sohrab V, López-Díaz C, Di Pietro A, Ma L-J, Ayhan DH. TEfinder: a bioinformatics pipeline for detecting new transposable element insertion events in next-generation sequencing data. Genes (Basel) 2021 12:224.
    doi: 10.3390/genes12020224pmc: PMC7914406pubmed: 33557410google scholar: lookup
  88. Collins AJ, Whitaker RJ. CRISPR comparison toolkit (CCTK): rapid identification, visualization, and analysis of CRISPR array diversity. bioRxiv .
    doi: 10.1101/2022.07.31.502198pmc: PMC10457644pubmed: 37459160google scholar: lookup
  89. Akhter S, Aziz RK, Edwards RA. Phispy: a novel algorithm for finding prophages in bacterial genomes that combines similarity- and composition-based strategies. Nucleic Acids Res 2012 40:e126.
    doi: 10.1093/nar/gks406pmc: PMC3439882pubmed: 22584627google scholar: lookup
  90. Kanehisa M, Furumichi M, Tanabe M, Sato Y, Morishima K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res 2017 45:D353–D361.
    doi: 10.1093/nar/gkw1092pmc: PMC5210567pubmed: 27899662google scholar: lookup
  91. 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.
    doi: 10.1038/s41467-018-07641-9pmc: PMC6269478pubmed: 30504855google scholar: lookup
  92. Chaudhari NM, Gupta VK, Dutta C. BPGA- an ultra-fast pan-genome analysis pipeline. Sci Rep 2016 6:24373.
    doi: 10.1038/srep24373pmc: PMC4829868pubmed: 27071527google scholar: lookup
  93. Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 2010 26:2460–2461.
    doi: 10.1093/bioinformatics/btq461pubmed: 20709691google scholar: lookup
  94. Pruitt KD, Tatusova T, Maglott DR. NCBI reference sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res 2005 33:D501–D504.
    doi: 10.1093/nar/gki025pmc: PMC539979pubmed: 15608248google scholar: lookup
  95. Xu Z, Hao B. CVTree update: a newly designed phylogenetic study platform using composition vectors and whole genomes. Nucleic Acids Res 2009 37:W174–W178.
    doi: 10.1093/nar/gkp278pmc: PMC2703908pubmed: 19398429google scholar: lookup
  96. Letunic I, Bork P. Interactive tree of life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res 2021 49:W293–W296.
    doi: 10.1093/nar/gkab301pmc: PMC8265157pubmed: 33885785google scholar: lookup
  97. Jung M-Y, Well R, Min D, Giesemann A, Park S-J, Kim J-G, Kim S-J, Rhee S-K. Isotopic signatures of N2O produced by ammonia-oxidizing archaea from soils. ISME J 2014 8:1115–1125.
    doi: 10.1038/ismej.2013.205pmc: PMC3996685pubmed: 24225887google scholar: lookup

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