Characterization of Klebsiella pneumoniae bacteriophages, KP1 and KP12, with deep learning-based structure prediction
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- Characterization of Klebsiella pneumoniae bacteriophages, KP1 and KP12, with deep learning-based structure prediction
- Kim, Youngju; Lee, Sang-Mok; Nong, Linh Khanh; Kim, Jaehyung; Kim, Seung Bum; Kim, Donghyuk
- Issue Date
- FRONTIERS MEDIA SA
- FRONTIERS IN MICROBIOLOGY, v.13, pp.990910
- Concerns over Klebsiella pneumoniae resistance to the last-line antibiotic treatment have prompted a reconsideration of bacteriophage therapy in public health. Biotechnological application of phages and their gene products as an alternative to antibiotics necessitates the understanding of their genomic context. This study sequenced, annotated, characterized, and compared two Klebsiella phages, KP1 and KP12. Physiological validations identified KP1 and KP12 as members of Myoviridae family. Both phages showed that their activities were stable in a wide range of pH and temperature. They exhibit a host specificity toward K. pneumoniae with a broad intraspecies host range. General features of genome size, coding density, percentage GC content, and phylogenetic analyses revealed that these bacteriophages are distantly related. Phage lytic proteins (endolysin, anti-/holin, spanin) identified by the local alignment against different databases, were subjected to further bioinformatic analyses including three-dimensional (3D) structure prediction by AlphaFold. AlphaFold models of phage lysis proteins were consistent with the published X-ray crystal structures, suggesting the presence of T4-like and P1/P2-like bacteriophage lysis proteins in KP1 and KP12, respectively. By providing the primary sequence information, this study contributes novel bacteriophages for research and development pipelines of phage therapy that ultimately, cater to the unmet clinical and industrial needs against K. pneumoniae pathogens.
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