This article is part of the supplement: Validation methods for functional genome annotation

Open Access Research

A nuclear magnetic resonance based approach to accurate functional annotation of putative enzymes in the methanogen Methanosarcina acetivorans

Yihong Chen1, Ethel Apolinario2, Libuse Brachova3, Zvi Kelman14, Zhuo Li1, Basil J Nikolau356, Lucas Showman6, Kevin Sowers2 and John Orban17*

Author Affiliations

1 Institute for Bioscience and Biotechnology Research, University of Maryland, 9600 Gudelsky Drive, Rockville MD 20850, USA

2 Department of Marine Biotechnology, University of Maryland Baltimore County, Baltimore MD, USA

3 Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames IA 50011, USA

4 Department of Cell Biology and Molecular Genetics, University of Maryland College Park, USA

5 Center for Biorenewable Chemicals, Iowa State University, Ames IA 50011, USA

6 Plant Sciences Institute, Iowa State University, Ames IA 50011, USA

7 Department of Chemistry and Biochemistry, University of Maryland College Park, USA

For all author emails, please log on.

BMC Genomics 2011, 12(Suppl 1):S7  doi:10.1186/1471-2164-12-S1-S7

Published: 15 June 2011

Additional files

Additional file 1:

List of revised MA annotations Annotations for genes between MA0001 and MA4675.

Format: PDF Size: 215KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

Additional file 2:

Summary of results for manually re-annotated MA genes. (a) Categorization of revised MA annotations as more specific, less specific or no change. (b) The distribution of confidence levels (defined in the text) in re-annotated MA genes.

Format: PDF Size: 242KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

Additional file 3:

List of forward and reverse primer DNA sequences used for cloning MA target genes.

Format: PDF Size: 124KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data