Whole-genome sequencing (WGS) of bacterial pathogens is widely conducted in microbiological, medical, and clinical research to explore genetic insights that could impact clinical treatment and molecular epidemiology. However, analyzing WGS data of bacteria can pose challenges for microbiologists, clinicians, and researchers, as it requires the application of several bioinformatics pipelines to extract genetic information from raw data. In this paper, we present BacSeq, an automated bioinformatic pipeline for the analysis of next-generation sequencing data of bacterial genomes. BacSeq enables the assembly, annotation, and identification of crucial genes responsible for multidrug resistance, virulence factors, and plasmids. Additionally, the pipeline integrates comparative analysis among isolates, offering phylogenetic tree analysis and identification of single-nucleotide polymorphisms (SNPs). To facilitate easy analysis in a single step and support the processing of multiple isolates, BacSeq provides a graphical user interface (GUI) based on the JAVA platform. It is designed to cater to users without extensive bioinformatics skills.
Lactic acid bacteria (LAB) in the genus Weissella spp. contain traits in their genome that confer versatility. In particular, Weissella cibaria encodes several beneficial genes that are useful in biotechnological applications. The complete genome of W. cibaria NH9449 was sequenced and an in silico comparative analysis was performed to gain insight into the genomic diversity among members of the genus Weissella. A total of 219 Weissella genomes were used in a bioinformatics analysis of pan-genomes, phylogenetics, self-defense mechanisms, virulence factors, antimicrobial resistance, and carbohydrate-active enzymes. These investigations showed that the strain NH9449 encodes several restriction-modification-related genes and a CRISPR-Cas region in its genome. The identification of carbohydrate-active enzyme-encoding genes indicated that this strain could be beneficial in biotechnological applications. The comparative genomic analysis reveals the very high genomic diversity in this genus, and some marked differences in genetic variation and genes among Weissella species. The calculated average amino acid identity (AAI) and phylogenetic analysis of core and accessory genes shows the possible existence of three new species in this genus. These new genomic insights into Weissella species and their biological functions could be useful in the food industry and other applications.
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