Development of a bioinformatics tool for identifying members of the Apis mellifera gut microbiome

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The methods of molecular genetics and bioinformatics analysis of DNA nucleotide sequences are reliable and modern tools for studying the microbiome of various organisms, including the gut microorganisms of Apis mellifera. The creation of accessible software for processing and analyzing sequencing data is highly relevant, as existing commercial solutions are often too expensive for widespread use in academic settings. Available free software typically has significant functional limitations, preventing comprehensive analysis. Researchers are often forced to use a combination of different software tools, which not only reduces data processing efficiency but also significantly increases the risk of errors during analysis. The rapid advancement of research on the A. mellifera gut microbiota, combined with the lack of accessible analytical tools for processing sequencing data, underscores the importance of developing software that automates the entire analysis process. The implementation of such a tool would not only simplify and accelerate sequencing data processing but also make it more accessible to a broader range of researchers, fostering the development of microbiome studies in honeybees and other organisms. The aim of the study was to develop bioinformatics software for automating the processing and analysis of nucleotide sequence data of the 16S rRNA gene and ITS region, to validate its performance, and to conduct a comparative evaluation based on the results of studying the gut microorganisms of A. mellifera. As part of the work, yeasts were isolated from the gut of A. mellifera, and DNA was extracted from these microorganisms. Amplification and sequencing of the 16S rRNA gene and ITS region were performed. Based on the obtained data, specialized bioinformatics software was developed, integrating all the necessary tools for comprehensive sequencing data analysis. The developed software was successfully validated on the obtained sequencing data. To assess its effectiveness, a comparative analysis was conducted with the widely recognized Geneious software, confirming the competitiveness and reliability of the developed tool.