Volume: 3, 2024
3rd International PhD Student’s Conference at the University of Life Sciences in Lublin, Poland:
ENVIRONMENT – PLANT – ANIMAL – PRODUCT
Abstract number: F013
DOI: https://doi.org/10.24326/ICDSUPL3.F013
Published online: 24 April 2024
ICDSUPL, 3, F013 (2024)
Bioinformatics in metagenomic food research
Jan Sadurski1*, Adam Waśko1
1 Department of Biotechnology, Microbiology and Human Nutrition, Faculty of Food Science and Biotechnology, University of Life Sciences In Lublin, Skromna 8, 20-704 Lublin, Poland
* Corresponding author: jan.sadurski@up.lublin.pl
Abstract
Currently, the majority of food is produced on an industrial scale, with its microbiological composition being limited and tightly controlled. Particularly, fermented food has a less diverse microflora, restricted to microorganisms introduced after prior sterilization of raw materials, for example, through pasteurization or UHT treatment of milk. Growing consumer awareness is pressuring producers to create functional foods containing probiotic organisms or their metabolic products, known as postbiotics. New probiotic organisms and postbiotic producers can be found in regional and traditional food. In their production, unprocessed raw materials with their own microflora are used, which can develop during the fermentation process. The challenge in isolating and further studying new strains from food lies in cultivating them on microbiological media. Replicating identical conditions present during the artisanal production and maturation processes can be time-consuming and costly. Metagenomics offers a solution to this problem. Metagenomics is a science that deals with the study of genetic material directly sampled from the environment. Unlike genomics, it does not require the prior cultivation of microorganisms on a culture medium. This field leverages high-throughput sequencing (HTS) technology, allowing for cost-effective and rapid DNA sequencing. The obtained metagenomes can be analyzed taxonomically and functionally, enabling the comparison of production strains with those found in regional foods. Metagenomics also facilitates the identification of the geographical origin of food and whether the production process aligns with the manufacturer’s claims. In recent years, we have witnessed a dynamic growth in bioinformatics solutions focusing on metagenomics analysis. Machine learning, particularly neural networks, is increasingly employed in these programs to shorten analysis times and improve result quality. Neural networks can analyze vast amounts of data and match metagenomic profiles to a specific product with much greater precision than basic statistical analysis, especially in non-linear data relationships.
Keywords: foodomics, bioinformatics, metagenomics, microbiome, food
How to cite
J. Sadurski, A. Waśko, 2024. Bioinformatics in metagenomic food research. In: 3rd International PhD Student’s Conference at the University of Life Sciences in Lublin, Poland: Environment – Plant – Animal – Product. https://doi.org/10.24326/ICDSUPL3.F013