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Lactiplantibacillus paraplantarum is a lactic acid bacteria species that is associated with food microbiomes and has been found to be either detrimental or beneficial against specific food processes. To augment our genomic understanding of L.paraplantarum and uncover metabolic differences and lifestyle adaptations between strains (DSM10667, L-ZS9, AS-7) to better utilize these species in food bioprocesses. In-silico genomic approach applied using JGI’s IMG/MER, and PATRIC to compare DSM10667, L-ZS9 and AS-7 genomes. Bacteriocin and prophage screenings were performed using Bagel4 and PHASTER software respectively. BRIG was used to identify alignments of strains to each other for visual inspection of each genome. KEGG was used to predict putative carbohydrate, pyruvate, and amino-acid metabolisms. Genome sizes of DSM10667, L-ZS9, and AS-7 were 3.36, 3.14 and 3.01 M bp, respectively. Unique genes were found to predict evolutionary adaptation of strains against their corresponding micro-niche. For example, the gene encoding arginase was only found in sausage isolate L-ZS9 while dextran-sucrase encoding gene was unique to beer contaminant DSM10667. All three strains predicted to carry plnAEFJ operon for plantaricin biosynthesis and AS-7 genome contains leucocin K. Although DSM 10667 harbors four intact prophages, both L-ZS9 and AS-7 carried one prophage region still showing the plasticity of the genome. Genome analysis predicted isolation sources might potentially affect the metabolic capabilities of strains part of adaptation of the strains to their habitats. Our findings put forth new insights into the genomics of L.paraplantarum for future studies and uncovering potential strain manipulation elements for better use in commercial processing environment.
Benk et al. (Tue,) studied this question.