Computational characterization and analysis of molecular sequence data of Elizabethkingia meningoseptica

Objective Elizabethkingia meningoseptica is a multidrug resistance strain which primarily causes meningitis in neonates and immunocompromised patients. Being a nosocomial infection causing agent, less information is available in literature, specifically, about its genomic makeup and associated features. An attempt is made to study them through bioinformatics tools with respect to compositions, embedded periodicities, open reading frames, origin of replication, phylogeny, orthologous gene clusters analysis and pathways. Results Complete DNA and protein sequence pertaining to E. meningoseptica were thoroughly analyzed as part of the study. E. meningoseptica G4076 genome showed 7593 ORFs it is GC rich. Fourier based analysis showed the presence of typical three base periodicity at the genome level. Putative origin of replication has been identified. Phylogenetically, E. meningoseptica is relatively closer to E. anophelis compared to other Elizabethkingia species. A total of 2606 COGs were shared by all five Elizabethkingia species. Out of 3391 annotated proteins, we could identify 18 unique ones involved in metabolic pathway of E. meningoseptica and this can be an initiation point for drug designing and development. Our study is novel in the aspect in characterizing and analyzing the whole genome data of E. meningoseptica.

Automated summary

This study analyzed the complete DNA and protein sequences of E. meningoseptica using bioinformatics tools. The results showed that E. meningoseptica has a GC-rich genome with a typical three-base periodicity. The putative origin of replication was identified, and phylogenetic analysis revealed a closer relationship between E. meningoseptica and E. anophelis. Additionally, 18 unique proteins involved in the metabolic pathway of E. meningoseptica were identified, which could serve as potential targets for drug design and development.