Back

From Sequence to Significance: A Thorough Investigation of the Distinctive Genome Traits Uncovered in C. werkmanii strain NIB003

Hossain, M. U.; Tanvir, N. K.; Chowdhury, Z. M.; Rahman, A. N.; Hossain, M. S.; Dey, S.; Bhattacharjee, A.; Ahmed, I.; Hashem, A.; Das, K. C.; Keya, C. A.; Salimullah, M.

2023-11-21 genomics
10.1101/2023.11.21.568014 bioRxiv
Show abstract

Citrobacter werkmanii (C. werkmanii) is an opportunistic bacterium that has received very little investigation in Bangladesh, even though it is thought to be capable of causing diseases including diarrhea and urinary tract infections. Therefore, the present study focuses on the exploration of genomic features, including antibiotic resistance genes, virulent genes, and their distinctive nature in the pathogenesis of diseases. A complete genome was sequenced for the first time in Bangladesh after the morphological, biochemical and molecular identification of this bacteria. A total of 47,65,861 nucleotide base pairs makes up the genome, which contains 4669 genes, and many of the protein-coding genes can be classified into various ontological frameworks, including COG and KEGG pathways. Notably, C. werkmanii has the capability to have interactions with Escherichia coli, Salmonella, and Klebsiella while they possess the same domains and motifs, indicating a causal role in the development of diarrhea. Furthermore, the Bangladeshi isolate of C. werkmaii has observed genetic heterogeneity when compared to other strains of C. werkmanii: C. werkmanii FDAARGOS_616, C. werkmanii LCU-V21, and C. werkmanii BF-6. This identified genetic variation of sequenced C. werkmanii could drive the functional aberration in body homeostasis of bacteria. Later, molecular dynamics studies have proven the impact of their genetic variation on the protein structure, as indicated by the SASA, RMSD, Rg, and RMSF values. Finally, the findings of C. werkmanii from the sequenced genome might provide us with a better understanding of C. werkmanii and their possible role as opportunistic bacteria in diseases including diarrhea and urinary tract infections.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.