Draft Genome Sequence of Klebsiella pneumoniae subsp. pneumoniae DSM 30104
            <sup>T</sup>

Lee, Jehee; Cheon, In Su; Shim, Byoung-Shik; Kim, Dong Wook; Kim, Suhng Wook; Chun, Jongsik; Song, Manki

doi:10.1128/jb.01388-12

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…This was confirmed by BLAST analysis which showed 100% identity with MdtG found in Klebsiella pneumoniae subsp. pneumoniae DSM 30104 which is experimentally proven to be involved in the multidrug resistance in Klebsiella pneumoniae DSM 30104 [ 32 ]. Similarly, tetracycline efflux protein found in Salmonella enterica was predicted to be in class 2, which was also supported by the BLAST results.…”

Section: Resultsmentioning

confidence: 99%

MP4: a machine learning based classification tool for prediction and functional annotation of pathogenic proteins from metagenomic and genomic datasets

et al. 2022

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Bacteria can exceptionally evolve and develop pathogenic features making it crucial to determine novel pathogenic proteins for specific therapeutic interventions. Therefore, we have developed a machine-learning tool that predicts and functionally classifies pathogenic proteins into their respective pathogenic classes. Through construction of pathogenic proteins database and optimization of ML algorithms, Support Vector Machine was selected for the model construction. The developed SVM classifier yielded an accuracy of 81.72% on the blind-dataset and classified the proteins into three classes: Non-pathogenic proteins (Class-1), Antibiotic Resistance Proteins and Toxins (Class-2), and Secretory System Associated and capsular proteins (Class-3). The classifier provided an accuracy of 79% on real dataset-1, and 72% on real dataset-2. Based on the probability of prediction, users can estimate the pathogenicity and annotation of proteins under scrutiny. Tool will provide accurate prediction of pathogenic proteins in genomic and metagenomic datasets providing leads for experimental validations. Tool is available at: http://metagenomics.iiserb.ac.in/mp4.

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Section: Resultsmentioning

confidence: 99%

MP4: a machine learning based classification tool for prediction and functional annotation of pathogenic proteins from metagenomic and genomic datasets

et al. 2022

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“…Where specified, Klebsiella spp. used here were derived from previous studies [25][26][27][28][29] and are listed in Table S1. All Klebsiella strains were cultured overnight on brain heart infusion (BHI) agar (Oxoid) at 37 °C.…”

Section: Bacterial Strains and Growth Conditionsmentioning

confidence: 99%

A hybrid and poly-polish workflow for the complete and accurate assembly of phage genomes: a case study of ten przondoviruses

et al. 2023

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Bacteriophages (phages) within the genus Przondovirus are T7-like podoviruses belonging to the subfamily Studiervirinae, within the family Autographiviridae, and have a highly conserved genome organisation. The genomes of these phages range from 37 to 42 kb in size, encode 50–60 genes and are characterised by the presence of direct terminal repeats (DTRs) flanking the linear chromosome. These DTRs are often deleted during short-read-only and hybrid assemblies. Moreover, long-read-only assemblies are often littered with sequencing and/or assembly errors and require additional curation. Here, we present the isolation and characterisation of ten novel przondoviruses targeting Klebsiella spp. We describe HYPPA, a HYbrid and Poly-polish Phage Assembly workflow, which utilises long-read assemblies in combination with short-read sequencing to resolve phage DTRs and correcting errors, negating the need for laborious primer walking and Sanger sequencing validation. Our assembly workflow utilised Oxford Nanopore Technologies for long-read sequencing for its accessibility, making it the more relevant long-read sequencing technology at this time, and Illumina DNA Prep for short-read sequencing, representing the most commonly used technologies globally. Our data demonstrate the importance of careful curation of phage assemblies before publication, and prior to using them for comparative genomics.

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A hybrid and poly-polish workflow for the complete and accurate assembly of phage genomes: a case study of ten przondoviruses

Elek

Brown

Viet

et al. 2023

Preprint

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Bacteriophages (phages) within the Przondovirus genus are T7-like podoviruses belonging to the Studiervirinae subfamily, within the Autographiviridae family and have a highly conserved genome organisation. The genome size of these phages ranges from 37 kb to 42 kb, encode 50-60 genes and are characterised by the presence of direct terminal repeats (DTRs) flanking the linear chromosome. These DTRs are often deleted during short-read-only and hybrid assemblies. Moreover, long-read-only assemblies are often littered with sequencing and/or assembly errors and require additional curation. Here, we present the isolation and characterisation of ten novel przondoviruses targeting Klebsiella spp. We describe HYPPA - a HYbrid and Poly-polish Phage Assembly workflow, which utilises long-read assemblies in combination with short-read sequencing to resolve phage DTRs and correcting errors, negating the need for laborious primer walking and Sanger sequencing validation. Our data demonstrate the importance of careful curation of phage assemblies before publication, and prior to using them for comparative genomics.

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Draft Genome Sequence of Klebsiella pneumoniae subsp. pneumoniae DSM 30104 ^T

Cited by 3 publications

References 15 publications

MP4: a machine learning based classification tool for prediction and functional annotation of pathogenic proteins from metagenomic and genomic datasets

MP4: a machine learning based classification tool for prediction and functional annotation of pathogenic proteins from metagenomic and genomic datasets

A hybrid and poly-polish workflow for the complete and accurate assembly of phage genomes: a case study of ten przondoviruses

A hybrid and poly-polish workflow for the complete and accurate assembly of phage genomes: a case study of ten przondoviruses

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Draft Genome Sequence of Klebsiella pneumoniae subsp. pneumoniae DSM 30104 T

Cited by 3 publications

References 15 publications

MP4: a machine learning based classification tool for prediction and functional annotation of pathogenic proteins from metagenomic and genomic datasets

MP4: a machine learning based classification tool for prediction and functional annotation of pathogenic proteins from metagenomic and genomic datasets

A hybrid and poly-polish workflow for the complete and accurate assembly of phage genomes: a case study of ten przondoviruses

A hybrid and poly-polish workflow for the complete and accurate assembly of phage genomes: a case study of ten przondoviruses

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Draft Genome Sequence of Klebsiella pneumoniae subsp. pneumoniae DSM 30104 ^T