Molecular evidence of Burkholderia pseudomallei genotypes based on geographical distribution

Background. Central intermediary metabolism (CIM) in bacteria is defined as a set of metabolic biochemical reactions within a cell, which is essential for the cell to survive in response to environmental perturbations. The genes associated with CIM are commonly found in both pathogenic and non-pathogenic strains. As these genes are involved in vital metabolic processes of bacteria, we explored the efficiency of the genes in genotypic characterization of Burkholderia pseudomallei isolates, compared with the established pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST) schemes. Methods. Nine previously sequenced B. pseudomallei isolates from Malaysia were characterized by PFGE, MLST and CIM genes. The isolates were later compared to the other 39 B. pseudomallei strains, retrieved from GenBank using both MLST and sequence analysis of CIM genes. UniFrac and hierachical clustering analyses were performed using the results generated by both MLST and sequence analysis of CIM genes. Results. Genetic relatedness of nine Malaysian B. pseudomallei isolates and the other 39 strains was investigated. The nine Malaysian isolates were subtyped into six PFGE profiles, four MLST profiles and five sequence types based on CIM genes alignment. All methods demonstrated the clonality of OB and CB as well as CMS and THE. However, PFGE showed less than 70% similarity between a pair of morphology variants, OS and OB. In contrast, OS was identical to the soil isolate, MARAN. To have a better understanding of the genetic diversity of B. pseudomallei worldwide, we further aligned the sequences of genes used in MLST and genes associated with CIM for the nine Malaysian isolates and 39 B. pseudomallei strains from NCBI database. Overall, based on the CIM genes, the strains were subtyped into 33 profiles where majority of the strains from Asian countries were clustered together. On the other hand, MLST resolved the isolates into 31 profiles which formed three clusters. Hierarchical clustering using UniFrac distance suggested that the isolates from Australia were genetically distinct from the Asian isolates. Nevertheless, statistical significant differences were detected between isolates from Malaysia, Thailand and Australia. Discussion. Overall, PFGE showed higher discriminative power in clustering the nine Malaysian B. pseudomallei isolates and indicated its suitability for localized epidemiological study. Compared to MLST, CIM genes showed higher resolution in distinguishing those non-related strains and better clustering of strains from different geographical regions. A closer genetic relatedness of Malaysian isolates with all Asian strains in comparison to Australian strains was observed. This finding was supported by UniFrac analysis which resulted in geographical segregation between Australia and the Asian countries.