Decoding the Gene Variants of Two Native Probiotic Lactiplantibacillus plantarum Strains through Whole-Genome Resequencing: Insights into Bacterial Adaptability to Stressors and Antimicrobial Strength

通过全基因组重测序解码两种天然益生菌植物乳杆菌菌株的基因变异:深入了解细菌对压力源的适应性和抗菌强度

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Abstract

In this study, whole-genome resequencing of two native probiotic Lactiplantibacillus plantarum strains-UTNGt21A and UTNGt2-was assessed in order to identify variants and perform annotation of genes involved in bacterial adaptability to different stressors, as well as their antimicrobial strength. A total of 21,906 single-nucleotide polymorphisms (SNPs) were detected in UTNGt21A, while 17,610 were disclosed in the UTNGt2 genome. The comparative genomic analysis revealed a greater number of deletions, transversions, and transitions within the UTNGt21A genome, while a small difference in the number of insertions was detected between the strains. A divergent number of types of variant annotations were detected in both strains, and categorized in terms of low, moderate, and high modifier impact on the protein effectiveness. Although both native strains shared common specific genes involved in the stress response to the gastrointestinal environment, which may qualify as a putative probiotic (bile salt, acid, temperature, osmotic stress), they were different in their antimicrobial gene cluster organization, with UTNGt21A displaying a complex bacteriocin gene arrangement and dissimilar gene variants that might alter their defense mechanisms and overall inhibitory capacity. The genome comparison revealed 34 and 9 genomic islands (GIs) in the UTNGt21A and UTNGt2 genomes, respectively, with the overrepresentation of genes involved in defense mechanisms and carbohydrate utilization. In addition, pan-genome analysis disclosed the presence of various strain-specific genes (shell genes), suggesting a high genome variation between strains. This genome analysis illustrates that the bacteriocin signature and gene variants reflect a niche-inherent pattern. These extensive genomic datasets will guide us to understand the potential benefits of the native strains and their utility in the food or pharmaceutical sectors.

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