Literature DB >> 34777930

Revealing the potential of Klebsiella pneumoniae PVN-1 for plant beneficial attributes by genome sequencing and analysis.

Varsha Jha1,2, Hemant Purohit1, Nishant A Dafale1,2.   

Abstract

Genome sequencing of Klebsiella pneumoniae PVN-1, isolated from effluent treatment plant (ETP), generates a 5.064 Mb draft genome with 57.6% GC content. The draft genome assembled into 19 contigs comprises 4783 proteins, 3 rRNA, 44 tRNA, 8 other RNA, 4911 genes, and 73 pseudogenes. Genome information revealed the presence of phosphate metabolism/solubilizing, potassium solubilizing, auxin production, and other plant benefiting attributes like enterobactin and pyrroloquinoline quinone biosynthesis genes. Presence of gcd and pqq genes in K. pneumoniae PVN-1 genome validates the inorganic phosphate solubilizing potential (528.5 mg/L). Pangenome analysis identified a unique 5'-Nucleotidase that further assists in enhanced phosphate acquisition. Additionally, the genetic potential for complete benzoate, catechol, and phenylacetate degradation with stress response and heavy metal (Cu, Zn, Ni, Co) resistance was identified in K. pneumoniae PVN-1. Functioning of annotated plant benefiting genes validates by the metabolic activity of auxin production (7.40 µg/mL), nitrogen fixation, catalase activity, potassium solubilization (solubilization index-3.47), and protease activity (proteolytic index-2.27). In conclusion, the K. pneumoniae PVN-1 genome has numerous beneficial qualities that can be employed to enhance plant growth as well as for phytoremediation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13205-021-03020-2. © King Abdulaziz City for Science and Technology 2021.

Entities:  

Keywords:  Functional genes; Genome characterization; Pangenome; Phosphate solubilization; Plant-growth attributes

Year:  2021        PMID: 34777930      PMCID: PMC8546017          DOI: 10.1007/s13205-021-03020-2

Source DB:  PubMed          Journal:  3 Biotech        ISSN: 2190-5738            Impact factor:   2.406


  31 in total

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Journal:  3 Biotech       Date:  2019-06-08       Impact factor: 2.406

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7.  BPGA- an ultra-fast pan-genome analysis pipeline.

Authors:  Narendrakumar M Chaudhari; Vinod Kumar Gupta; Chitra Dutta
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Review 8.  A Review of Dynamic Modeling Approaches and Their Application in Computational Strain Optimization for Metabolic Engineering.

Authors:  Osvaldo D Kim; Miguel Rocha; Paulo Maia
Journal:  Front Microbiol       Date:  2018-07-31       Impact factor: 5.640

9.  Beneficial bacteria activate nutrients and promote wheat growth under conditions of reduced fertilizer application.

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Journal:  BMC Microbiol       Date:  2020-02-21       Impact factor: 3.605

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