Article abstract


Nature Biotechnology 25, 569 - 575 (2007)
Published online: 29 April 2007 | doi:10.1038/nbt1302

Genome sequence and identification of candidate vaccine antigens from the animal pathogen Dichelobacter nodosus

Garry S A Myers1,8, Dane Parker2,3,4,8, Keith Al-Hasani2,3, Ruth M Kennan2,3, Torsten Seemann4, Qinghu Ren1, Jonathan H Badger1, Jeremy D Selengut1, Robert T DeBoy1, Hervé Tettelin1, John D Boyce2,3, Victoria P McCarl2,5, Xiaoyan Han2,3, William C Nelson1, Ramana Madupu1, Yasmin Mohamoud1, Tara Holley1, Nadia Fedorova1, Hoda Khouri1, Steven P Bottomley2,5, Richard J Whittington2,6, Ben Adler2,3,4, J Glenn Songer5, Julian I Rood2,3,4 & Ian T Paulsen1


Dichelobacter nodosus causes ovine footrot, a disease that leads to severe economic losses in the wool and meat industries. We sequenced its 1.4-Mb genome, the smallest known genome of an anaerobe. It differs markedly from small genomes of intracellular bacteria, retaining greater biosynthetic capabilities and lacking any evidence of extensive ongoing genome reduction. Comparative genomic microarray studies and bioinformatic analysis suggested that, despite its small size, almost 20% of the genome is derived from lateral gene transfer. Most of these regions seem to be associated with virulence. Metabolic reconstruction indicated unsuspected capabilities, including carbohydrate utilization, electron transfer and several aerobic pathways. Global transcriptional profiling and bioinformatic analysis enabled the prediction of virulence factors and cell surface proteins. Screening of these proteins against ovine antisera identified eight immunogenic proteins that are candidate antigens for a cross-protective vaccine.

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  1. The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, Maryland 20850, USA.
  2. Australian Research Council Centre of Excellence in Structural and Functional Microbial Genomics, Monash University, Melbourne, Victoria 3800, Australia.
  3. Department of Microbiology, Monash University, Melbourne, Victoria 3800, Australia.
  4. Victorian Bioinformatics Consortium, Monash University, Melbourne, Victoria 3800, Australia.
  5. Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Victoria 3800, Australia.
  6. Faculty of Veterinary Science, University of Sydney, Sydney, New South Wales 2570, Australia.
  7. Department of Veterinary Science, University of Arizona, Tucson, Arizona 85721, USA.
  8. These authors contributed equally to this work.

Correspondence to: Ian T Paulsen1 e-mail: ipaulsen@tigr.org



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