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Nature Biotechnology
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The genome sequence of the capnophilic rumen bacteriumMannheimia succiniciproducens

Nature Biotechnologyvolume 22pages1275–1281 (2004)Cite this article

ACorrigendum to this article was published on 01 December 2004

Abstract

The rumen represents the first section of a ruminant animal's stomach, where feed is collected and mixed with microorganisms for initial digestion. The major gas produced in the rumen is CO2 (65.5 mol%), yet the metabolic characteristics of capnophilic (CO2-loving) microorganisms are not well understood. Here we report the 2,314,078 base pair genome sequence ofMannheimia succiniciproducens MBEL55E, a recently isolated capnophilic Gram-negative bacterium from bovine rumen, and analyze its genome contents and metabolic characteristics. The metabolism ofM. succiniciproducens was found to be well adapted to the oxygen-free rumen by using fumarate as a major electron acceptor. Genome-scale metabolic flux analysis indicated that CO2 is important for the carboxylation of phosphoenolpyruvate to oxaloacetate, which is converted to succinic acid by the reductive tricarboxylic acid cycle and menaquinone systems. This characteristic metabolism allows highly efficient production of succinic acid, an important four-carbon industrial chemical.

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Figure 1: Circular representation of theM. succiniciproducens MBEL55E genome.
Figure 2: Comparison ofM. succiniciproducens MBEL55E ORFs with other organisms.
Figure 3: Results of metabolic flux analyses.
Figure 4: Effects of various metabolic fluxes on the succinic acid fluxes examined by Bayesian network analysis.

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References

  1. Sniffen, C.J. & Herdt, H.H.The Veterinary Clinics of North America: Food Animal Practice (W.B. Saunders Company, Pennsylvania, USA, 1991).

    Google Scholar 

  2. Lee, P.C., Lee, S.Y., Hong, S.H. & Chang, H.N. Isolation and characterization of a new succinic acid-producing bacterium,Mannheimia succiniciproducens MBEL55E, from bovine rumen.Appl. Microbiol. Biotechnol.58, 663–668 (2002).

    Article CAS  Google Scholar 

  3. Lee, S.Y., Hong, S.H., Lee, S.H. & Park, S.J. Fermentative production of chemicals that can be used for polymer synthesis.Macromol. Biosci.4, 157–164 (2004).

    Article CAS  Google Scholar 

  4. Salzberg, S.L., Salzberg, A.J., Kerlavage, A.R. & Tomb, J.F. Skewed oligomers and origins of replication.Gene217, 57–67 (1998).

    Article CAS  Google Scholar 

  5. Blattner, F.R. et al. The complete genome sequence ofEscherichia coli K–12.Science277, 1453–1462 (1997).

    Article CAS  Google Scholar 

  6. Kunst, F. et al. The complete genome sequence of the gram-positive bacteriumBacillus subtilis.Nature390, 249–256 (1997).

    Article CAS  Google Scholar 

  7. May, B.J. et al. Complete genomic sequence ofPasteurella multocida, Pm70.Proc. Natl. Acad. Sci. USA98, 3460–3465 (2001).

    Article CAS  Google Scholar 

  8. Kanehisa, M., Goto, S., Kawashima, S. & Nakaya, A. The KEGG databases at GenomeNet.Nucleic Acids Res.30, 42–46 (2002).

    Article CAS  Google Scholar 

  9. Karp, P.D. Pathway databases: a case study in computational symbolic theories.Science293, 2040–2044 (2001).

    Article CAS  Google Scholar 

  10. Fleischmann, R.D. et al. Whole–genome random sequencing and assembly ofHaemophilus influenzae Rd.Science269, 496–512 (1995).

    Article CAS  Google Scholar 

  11. Angen, Ø., Mutters, R., Caugant, D.A., Olsen, J.E. & Bisgaard, M. Taxonomic relationships of the [Pasteurella]haemolytica complex as evaluated by DNA-DNA hybridizations and 16S rRNA sequencing with proposal ofMannheimia haemolytica gen. nov., comb. nov.,Mannheimia granulomatis comb. nov.,Mannheimia glucosida sp. nov.,Mannheimia ruminalis sp. nov. andMannheimia varigena sp. nov.Int. J. Syst. Bacteriol.49, 67–86 (1999).

    Article CAS  Google Scholar 

  12. Osawa, R. et al.Lonepinella koalarum gen. nov., sp. nov., a new tannin-protein complex degrading bacterium.Syst. Appl. Microbiol.18, 368–373 (1995).

    Article CAS  Google Scholar 

  13. Guettler, M.V., Rumler, D. & Jain, M.K.Actinobacillus succinogenes sp. nov., a novel succinic-acid-producing strain from the bovine rumen.Int. J. Syst. Bacteriol.49, 207–216 (1999).

    Article CAS  Google Scholar 

  14. Church, D.C.The Ruminant Animal: Digestive Physiology and Nutrition (Prentice Hall, New Jersey, USA, 1988).

    Google Scholar 

  15. Ibarra, R.U., Edwards, J.S. & Palsson, B.O.Escherichia coli K-12 undergoes adaptive evolution to achievein silco predicted optimal growth.Nature420, 186–189 (2002).

    Article CAS  Google Scholar 

  16. Edwards, J.S., Ibarra, R.U. & Palsso, B.O.In silico predictions ofEscherichia coli metabolic capabilities are consistent with experimental data.Nat. Biotechnol.19, 125–130 (2001).

    Article CAS  Google Scholar 

  17. Price, N.D., Papin, J.A., Schilling, C.H. & Palsson, B.O. Genome-scale microbialin silico models: the constraints-based approach.Trends Biotechnol.21, 162–169 (2003).

    Article CAS  Google Scholar 

  18. Favello, A., Hillier, L. & Wilson, R.K. Genomic DNA sequencing methods.Methods Cell Biol.48, 551–569 (1995).

    Article CAS  Google Scholar 

  19. Sambrook, J., Fritsch, E.F. & Maniatis, T.Molecular Cloning (Cold Spring Harbor Laboratory Press, Cold Spring Harbor, New York, 1989).

    Google Scholar 

  20. Gordon, D., Abajian, C. & Green, P. Consed: a graphical tool for sequence finishing.Genome Res.8, 195–202 (1998).

    Article CAS  Google Scholar 

  21. Delcher, A.L., Harmon, D., Kasif, S., White, O. & Salzberg, S.L. Improved microbial gene identification with GLIMMER.Nucleic Acids Res.27, 4636–4641 (1999).

    Article CAS  Google Scholar 

  22. Rutherford, K. et al. Artemis: sequence visualization and annotation.Bioinformatics16, 944–945 (2000).

    Article CAS  Google Scholar 

  23. Altschul, S.F., Gish, W., Miller, W., Myers, E.W. & Lipman, D.J. Basic local alignment search tool.J. Mol. Biol.215, 403–410 (1990).

    Article CAS  Google Scholar 

  24. Eddy, S.R. Profile hidden Markov models.Bioinformatics14, 755–763 (1998).

    Article CAS  Google Scholar 

  25. Tatusov, R.L. et al. The COG database: new developments in phylogenetic classification of proteins from complete genomes.Nucleic Acids Res.29, 22–28 (2001).

    Article CAS  Google Scholar 

  26. Lowe, T.M. & Eddy, S.R. tRNAscan–SE: a program for improved detection of transfer RNA genes in genomic sequence.Nucleic Acids Res.25, 955–964 (1997).

    Article CAS  Google Scholar 

  27. Varma, A. & Palsson, B.O. Metabolic flux balancing—basic concepts, scientific and practical use.Bio/Technology12, 994–998 (1994).

    Article CAS  Google Scholar 

  28. Neidhardt, F.C. & Umbarger, H.E. inEscherichia coli and Salmonella: Cellular and Molecular Biology, edn. 2 (ed. Neidhardt, F.C.) 13–16 (ASM Press, Washington, DC, 1996).

    Google Scholar 

  29. Lee, D.Y., Yun, H., Park, S. & Lee, S.Y. MetaFluxNet: the management of metabolic reaction information and quantitative metabolic flux analysis.Bioinformatics19, 2144–2146 (2003).

    Article CAS  Google Scholar 

  30. Eisen, M.B., Spellman, P.T., Brown, P.O. & Botstein, D. Cluster analysis and display of genome-wide expression patterns.Proc. Natl. Acad. Sci. USA95, 14863–14868 (1998).

    Article CAS  Google Scholar 

  31. Bradford, M.M. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding.Anal. Biochem.72, 248–254 (1976).

    Article CAS  Google Scholar 

  32. Burton, K. A study of the conditions and mechanism of the diphenylamine reaction for the colorimetric estimation of deoxyribonucleic acid.Biochem. J.62, 314–323 (1956).

    Google Scholar 

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Acknowledgements

We thank Sung Ho Goh and Heyung Ju Shin at the KRIBB, Young Ho Moon, Kang Ryul Choi, Sun Ho Cha, Sung Soo Kim, Soo Hyun Jeong, Eun Mi Chung and Sun Rye Jung at GenoTech, and Jinyoung Park, Sujin Chae and Hee Sun Chung at Bioinfomatix for their contributions during genome sequencing and annotation. This work was supported by the Korean Systems Biology Research Program (M10309020000-03B5002-00000) of the Ministry of Science and Technology (MOST), Bioinfomatix and by the Brain Korea 21 Project. Further support through the LG Chem Chair Professorship and IBM SUR program is appreciated.

Author information

Author notes
  1. Soon Ho Hong and Jin Sik Kim: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Chemical and Biomolecular Engineering, Department of BioSystems, Metabolic and Biomolecular Engineering National Research Laboratory, BioProcess Engineering Research Center and Bioinformatics Research Center, Korea Advanced Institute of Science and Technology, 373–1 Guseong-dong, Yuseong-gu, Daejeon, 305–701, Republic of Korea

    Soon Ho Hong, Jin Sik Kim & Sang Yup Lee

  2. Bioinfomatix, Inc., The fifth floor, Nam Chang Bldg., 748–162 Yeoksam-dong, Gangnam-gu, Seoul, 135–925, Republic of Korea

    Yong Ho In & Sun Shim Choi

  3. Korea Research Institute of Bioscience and Biotechnology (KRIBB), 52 Oun-dong, Yuseong-gu, Daejeon, 305–333, Republic of Korea

    Jeong-Keun Rih, Chang Hoon Kim, Haeyoung Jeong & Cheol Goo Hur

  4. GenoTech Corp., 461–6 Jeonmin-dong, Yuseong-gu, Daejeon, 305–390, Republic of Korea

    Haeyoung Jeong & Jae Jong Kim

  5. IDRTech Inc., 461–6 Jeonmin-dong, Yuseong-gu, Daejeon, 305–390, Republic of Korea

    Yong Ho In

Authors
  1. Soon Ho Hong
  2. Jin Sik Kim
  3. Sang Yup Lee
  4. Yong Ho In
  5. Sun Shim Choi
  6. Jeong-Keun Rih
  7. Chang Hoon Kim
  8. Haeyoung Jeong
  9. Cheol Goo Hur
  10. Jae Jong Kim

Corresponding author

Correspondence toSang Yup Lee.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Fig. 1

M. succiniciproducens MBEL55E genome characteristics. (PDF 956 kb)

Supplementary Fig. 2

A schematic diagram of the entire metabolic network. (PDF 170 kb)

Supplementary Fig. 3

Comparative analysis of the respiratory systems in various microorganisms. (PDF 150 kb)

Supplementary Fig. 4

Time profiles of batch fermentation under various conditions. (PDF 38 kb)

Supplementary Table 1

List ofM. succiniciproducens MBEL55E genes. (PDF 214 kb)

Supplementary Table 2

Functional analysis ofM. succiniciproducens MBEL55E genome. (PDF 52 kb)

Supplementary Table 3

Thein silico metabolic network. (PDF 98 kb)

Supplementary Table 4

Utilization of various carbon sources. (PDF 21 kb)

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Hong, S., Kim, J., Lee, S.et al. The genome sequence of the capnophilic rumen bacteriumMannheimia succiniciproducens.Nat Biotechnol22, 1275–1281 (2004). https://doi.org/10.1038/nbt1010

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