A Short Review on Harnessing Bioinformatics for Food Safety: Computational Approaches to Detecting Foodborne Pathogens
DOI:
https://doi.org/10.59247/jahir.v2i3.296Keywords:
Bioinformatics, Foodborne Pathogens, Next-Generation Sequencing, Machine Learning in Food Safety, Whole Genome SequencingAbstract
Foodborne diseases remain a significant global public health concern, affecting millions annually and causing substantial economic losses. Traditional microbiological methods for pathogen detection, such as culture-based identification and polymerase chain reaction, are often time-consuming and lack sensitivity. The integration of bioinformatics and high-throughput sequencing technologies, including next-generation sequencing and metagenomics, has revolutionized foodborne pathogen detection by enabling rapid, accurate, and culture-independent identification. Machine learning and artificial intelligence further enhance food safety monitoring through predictive modeling and risk assessment, facilitating early outbreak detection and improved contamination control. Whole genome sequencing has emerged as a gold standard for public health surveillance, allowing for precise pathogen characterization and antimicrobial resistance tracking. Data-sharing networks, such as GenomeTrakr and PulseNet, have strengthened global collaboration, enhancing real-time pathogen monitoring. However, challenges persist in data integration, technical expertise, and infrastructure development, which hinder the widespread adoption of these technologies. Addressing these barriers requires standardized protocols, AI-driven predictive models, and interdisciplinary collaboration between public health, industry, and academia. As bioinformatics continues to evolve, its role in pathogen surveillance, outbreak prevention, and food safety management will become increasingly vital. Advancements in bioinformatics tools and AI-driven approaches will ensure a more efficient, data-driven, and globally coordinated response to foodborne disease threats
References
I. I. Koire, “Food-Borne Diseases,” in Food Safety, Istanbul: Nobel Tip Kitabevleri, 2024, pp. 267–288. doi: 10.69860/nobel.9786053358787.18.
Y. Zhao et al., “Application of recombinase polymerase amplification with lateral flow assay to pathogen point-of-care diagnosis,” Front Cell Infect Microbiol, vol. 14, Nov. 2024, doi: 10.3389/fcimb.2024.1475922.
K. S. Algrooni, H. M. Alhaidan, H. A. Hamzah, M. F. Almarzouqi, and A. M. Hamad, “Innovative approaches to microbial identification enhancing accuracy and speed in infectious disease diagnostics,” Int J Community Med Public Health, vol. 11, no. 8, pp. 3231–3234, Jul. 2024, doi: 10.18203/2394-6040.ijcmph20241966.
P. M. Thwe, P. Ren, and M. Loeffelholz, “Genomic analysis of microbial infections,” in Molecular Medical Microbiology, Elsevier, 2024, pp. 1907–1929. doi: 10.1016/B978-0-12-818619-0.00063-0.
J. Sadurski, M. Polak-Berecka, A. Staniszewski, and A. Waśko, “Step-by-Step Metagenomics for Food Microbiome Analysis: A Detailed Review,” Foods, vol. 13, no. 14, p. 2216, Jul. 2024, doi: 10.3390/foods13142216.
S. Oh, H. Byeon, and J. Wijaya, “Machine learning surveillance of foodborne infectious diseases using wastewater microbiome, crowdsourced, and environmental data,” Water Res, vol. 265, p. 122282, Nov. 2024, doi: 10.1016/j.watres.2024.122282.
M. W. Allard et al., “Molecular Techniques in Foodborne Disease Surveillance,” in Encyclopedia of Food Safety, Elsevier, 2024, pp. 61–85. doi: 10.1016/B978-0-12-822521-9.00198-2.
S. Naydenova, L. de Luca, and S. Yamadjako, “Envisioning the expertise of the future†,” EFSA Journal, vol. 17, Jul. 2019, doi: 10.2903/j.efsa.2019.e170721.
M. A. Soliman, M. S. Azab, H. A. Hussein, M. M. Roushdy, and M. N. Abu el-naga, “FBPP: software to design PCR primers and probes for nucleic acid base detection of foodborne pathogens,” Sci Rep, vol. 14, no. 1, p. 1229, Jan. 2024, doi: 10.1038/s41598-024-51372-5.
C. Billington, J. M. Kingsbury, and L. Rivas, “Metagenomics Approaches for Improving Food Safety: A Review,” J Food Prot, vol. 85, no. 3, pp. 448–464, Mar. 2022, doi: 10.4315/JFP-21-301.
G. Banerjee et al., “Application of advanced genomic tools in food safety rapid diagnostics: challenges and opportunities,” Curr Opin Food Sci, vol. 47, p. 100886, Oct. 2022, doi: 10.1016/j.cofs.2022.100886.
A. Cabal et al., “Whole Genome Sequencing for Food Safety, Clinical and Public Health Microbiology,” 2024, pp. 865–873. doi: 10.1007/978-3-031-49062-0_90.
L. Sheng, J. Ji, X. Song, X. Wu, and X. Sun, “Advances in Artificial Intelligence-Assisted Proactive Prevention and Control of Food Safety,” Journal of Chinese Institute of Food Science and Technology, vol. 24, no. 10, pp. 14–27, 2024, doi: 10.16429/j.1009-7848.2024.10.002.
K. Ntakirutimana G., “The Use of AI in Predicting Disease Outbreaks,” Research Output Journal of Biological and Applied Science, vol. 4, no. 2, pp. 19–22, Sep. 2024, doi: 10.59298/ROJBAS/2024/421922.
K. Gensheimer et al., “Genomic Surveillance of Foodborne Pathogens: Advances and Obstacles,” Journal of Public Health Management & Practice, Nov. 2024, doi: 10.1097/PHH.0000000000002090.
V. Zatsu et al., “Revolutionizing the food industry: The transformative power of artificial intelligence-a review,” Food Chem X, vol. 24, p. 101867, Dec. 2024, doi: 10.1016/j.fochx.2024.101867.
M. Begley and C. Hill, “Food Safety: What Can We Learn From Genomics?,” Annu Rev Food Sci Technol, vol. 1, no. 1, pp. 341–361, Apr. 2010, doi: 10.1146/annurev.food.080708.100739.
M. D. Weinroth, B. C. Britton, and K. E. Belk, “Genetics and microbiology of meat,” Meat Sci, vol. 144, pp. 15–21, Oct. 2018, doi: 10.1016/j.meatsci.2018.04.017.
B. Imanian et al., “The power, potential, benefits, and challenges of implementing high-throughput sequencing in food safety systems,” NPJ Sci Food, vol. 6, no. 1, p. 35, Aug. 2022, doi: 10.1038/s41538-022-00150-6.
J. Kovac, “Precision Food Safety: a Paradigm Shift in Detection and Control of Foodborne Pathogens,” mSystems, vol. 4, no. 3, Jun. 2019, doi: 10.1128/mSystems.00164-19.
H. G. Kristinsson and H. Ó. Jörundsdóttir, “Food in the bioeconomy,” Trends Food Sci Technol, vol. 84, pp. 4–6, Feb. 2019, doi: 10.1016/j.tifs.2018.10.011.
L. Deblais, D. Kathayat, Y. A. Helmy, G. Closs, and G. Rajashekara, “Translating ‘big data’: better understanding of host-pathogen interactions to control bacterial foodborne pathogens in poultry,” Anim Health Res Rev, vol. 21, no. 1, pp. 15–35, Jun. 2020, doi: 10.1017/S1466252319000124.
U. Andjelković, M. Šrajer Gajdošik, D. Gašo-Sokač, T. Martinović, and D. Josić, “Foodomics and Food Safety: Where We Are,” Food Technol Biotechnol, vol. 55, no. 3, 2017, doi: 10.17113/ftb.55.03.17.5044.
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