Abstract:
Next generation of sequencing (NGS) technologies have taken life science research into a new era. With the rapid advances in these technologies and the associated reduction in overall costs, the sequencing and assembly of genomes have come within reach of most laboratories. Studies related to the evolution, ecology and biology of an organism now rely heavily on genomic data and obtaining a genome sequence has become an essential resource for the rapid progress and success of these studies. Pantoea ananatis is recognised as an emerging but rather unconventional pathogen capable of infecting a wide range of different hosts. Numerous plants of agricultural and economic importance including maize, rice, onion, pineapple, melon, sudan grass and Eucalyptus trees have been affected. With the outbreak of P. ananatis in a South African Eucalyptus nursery in 1998, it was realised that very little is known about this pathogen. A better understanding of the pathogenicity, metabolism and ecology of the bacterium is required to develop strategies for the control of the disease. During this study, the genome sequence of P. ananatis strain LMG 20103 was obtained using the Roche 454 technology. To aid in the assembly of this Eucalyptus pathogen’s genome sequence, the type strain of P. ananatis LMG 2665 was also sequenced using Illinima’s Genome Analyzer (GA). A draft assembly of P. ananatis LMG 20103, consisting of 117 contigs, was generated after optimization of the Newbler assembly parameters and comparison with other genome assemblies and genomes. This study demonstrated that the assembly could be completed using both in-vitro, and in-silico approaches such as contig scaffolding, gap closure with conventional PCR reactions and sequencing, manual curation and automated genome annotation. The final complete genome consisted of a 4 386 227 bp chromosome and a 317 146 bp mega-plasmid. With the complete genome sequence available, the reconstruction of metabolic network of P. ananatis LMG 20103 was attempted using two pathways reconstruction pipelines namely, Pathway Tools and Model SEED. It was found that missing metabolic reactions and incomplete pathways in the draft metabolic networks were mainly caused by incorrect gene annotations or bioinformatic errors during the automated network reconstruction. These two pipelines differed substantially in the way network reconstruction is undertaken. Performing a comparison between the two proposed networks, annotation errors could be detected and corrected. Although some improvement could be made to the predicted network further experimental data is still required to improve the accuracy of the draft metabolic network. Despite the amount of effort and cost, it is believed that the complete genome and a draft metabolic network of P. ananatis LMG 20103 will be a valuable resource for many subsequent studies to investigate the evolution and biology of this emerging plant pathogen. This information will be essential for the development of strategies to predict and control future disease outbreaks associated with this pathogen.
