Akademik Veri Yönetim Sistemi
International Food Innovation and Sustainability Congress, İstanbul, Türkiye, 16 - 18 Mayıs 2024, ss.212
Analysis can be performed to identify new gene clusters from the large amounts of data produced by nextgeneration sequencing technologies. In silico-based bioinformatic strategies can be established to identify new gene clusters from these data. Numerous data from complex microbiota contain a lot of information that can be analyzed as a result of DNA sequencing. Additionally, in-depth investigation of complex microbiotas in foods ensures food quality and sustainability. With the genome mining approach, many bacterial species and related genes that have the potential to produce a particular gene can be identified from shotgun metagenome datasets obtained from public genome databases. These genes may be peptides with various antimicrobial properties. One of the most common antimicrobial compounds produced by bacteria is bacteriocins. With genome mining, a wide variety of bacteria that have the potential to produce bacteriocins in the fermentation environment can be identified. Many interpretations can be made about the bacteriocins found in the samples that diversify the microbiota during the development period of the sample. There is a need to investigate complex microbiotas in which bacteriocin genes play a role. In this study, a screening strategy for a specific gene was created from shotgun metagenomic sequences, bioinformatic tools were examined and a review of their combined use was presented.
Keywords: Bacteriocin, fermentation microbiota, genome mining, bioinformatic, sustainability.