Int J Biol Sci 2008; 4(5):309-317. doi:10.7150/ijbs.4.309

Research Paper

A combined computational-experimental analyses of selected metabolic enzymes in Pseudomonas species

Deepak Perumal1,2, Chu Sing Lim1,2, Vincent T.K. Chow3, Kishore R. Sakharkar2,4, Meena K. Sakharkar1,2 ✉

1. Advanced Design and Modeling Lab, Nanyang Technological University, Singapore.
2. Biopharmaceutical Engineering Cluster, BioMedical Engineering Research Centre, Nanyang Technological University, Singapore.
3. Department of Microbiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
4. OmicsVista, Singapore.

This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) License. See for full terms and conditions.
Perumal D, Lim CS, Chow VTK, Sakharkar KR, Sakharkar MK. A combined computational-experimental analyses of selected metabolic enzymes in Pseudomonas species. Int J Biol Sci 2008; 4(5):309-317. doi:10.7150/ijbs.4.309. Available from

File import instruction


Comparative genomic analysis has revolutionized our ability to predict the metabolic subsystems that occur in newly sequenced genomes, and to explore the functional roles of the set of genes within each subsystem. These computational predictions can considerably reduce the volume of experimental studies required to assess basic metabolic properties of multiple bacterial species. However, experimental validations are still required to resolve the apparent inconsistencies in the predictions by multiple resources. Here, we present combined computational-experimental analyses on eight completely sequenced Pseudomonas species. Comparative pathway analyses reveal that several pathways within the Pseudomonas species show high plasticity and versatility. Potential bypasses in 11 metabolic pathways were identified. We further confirmed the presence of the enzyme O-acetyl homoserine (thiol) lyase (EC: in P. syringae pv. tomato that revealed inconsistent annotations in KEGG and in the recently published SYSTOMONAS database. These analyses connect and integrate systematic data generation, computational data interpretation, and experimental validation and represent a synergistic and powerful means for conducting biological research.

Keywords: Comparative microbial genomics, metabolic pathways, KEGG, Pseudomonas species, integrative biology, drug discovery.