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Functional Genome Prediction and Genome-Scale Metabolic Modeling of the Rhizobacteria Serratia liquefaciens Strain
Cristina Karina Andrade Alvarado1, Zoila Felipa Honorio Durand2, Sergio Eduardo Contreras-Liza1
1Departamento de Agronomía, Universidad Nacional José Faustino Sánchez Carrión (UNJFSC), Lima 15136, Peru.
Background/Objectives:
Serratia liquefaciens is a bacterium commonly found in the rhizosphere and may possess PGPR capabilities. The present study aimed to elucidate the genomic, phylogenomic, and metabolic characteristics of S. liquefaciens strain UNJFSC002 to determine whether it is an effective PGPR.
Methods:
The genome of strain UNJFSC002 was obtained from NCBI and annotated using Prokka. Functional genome prediction, phylogenetic reconstruction, and comparative genomics were performed using bioinformatics tools. A GEM model was reconstructed to simulate metabolic fluxes associated with nitrogen fixation, phosphate solubilization, and phytohormone biosynthesis. Computational phenotyping and in silico functional validation were also performed.
Results:
The draft genome (5.19 Mb, GC 55.33%) contained 4792 protein-coding genes, 4 rRNAs, and 81 tRNAs, with 100% completeness. ANI and core genome phylogeny confirmed its taxonomic position within S. liquefaciens, with an identity higher than 98.8%. Pangenome analysis of 25 Serratia genomes revealed an open and highly dynamic pangenome (30,515 orthologous groups), indicating extensive genetic plasticity. Functional annotation identified key genes associated with nitrogen and phosphate acquisition, as well as the biosynthesis of IAA and GABA, findings that were supported by GEM simulations, reinforcing its potential as a biofertilizer.
Conclusions:
The genomic approach confirmed that strain UNJFSC002 harbors multiple active genes and metabolic pathways associated with plant growth promotion and environmental resilience.
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