Foodomics approaches to facilitate the verification of the authenticity of foods: a possible strategy to screen, validate, and standardize food matrices.

Autores/as

  • Nurpudji Astuti Taslim Clinical Nutrition, Faculty of Medicine, Hasanuddin University, Indonesia.
  • Fahrul Nurkolis Biological Sciences, State Islamic University of Sunan Kalijaga (UIN Sunan Kalijaga) https://orcid.org/0000-0003-2151-0854
  • Hardinsyah Hardinsyah Department of Applied Nutrition, IPB University, Bogor, Indonesia
  • Vincentius Mario Yusuf Medical Programme, Faculty of Medicine, Brawijaya University, Malang, Indonesia
  • William Ben Gunawan Nutrition Science Department, Faculty of Medicine, Diponegoro University, Semarang, Indonesia
  • Mrinal Samtiya Department of Nutrition Biology, Central University of Haryana, Mahendragarh, India
  • Nelly Mayulu Faculty of Medicine, Sam Ratulangi University, Manado, Indonesia
  • Youla A. ASSA
  • Trina Ekawati Tallei Biology, Faculty of Mathematics and Natural Sciences, Sam Ratulangi University, Manado, Indonesia

DOI:

https://doi.org/10.12873/431hardinsyah

Palabras clave:

Foodomics, Food Authenticity, Food Matrices, Food Science, Biosensor

Resumen

The complexity of globalization, including the global food trade market, has the side effect that various raw foodstuffs are vulnerable to intentional and unintentional adulteration. However, food validation and standardization approaches are still unclear and challenging and need to be explored. Through this opinion article, the author would like to introduce a foodomics approach (Food, -Omics) to facilitate integrated food authenticity verification through biosensors. This approach is potentially suitable and offers more valuable accuracy as it combines biological analysis methods spanning genomics, transcriptomics, proteomics, and metabolomics. Meanwhile, several subdisciplines of Foodomics, such as metallomics, volatomics, and lipidomics, which are considered feasible to facilitate the verification of food authenticity, are also explored in this critical opinion. Foodomics consists of four main omics technologies, namely genomics, transcriptomics, proteomics, and metabolomics. This is an integration of promising approaches to provide standardized food matrices, thus becoming the most likely strategy to verify the authenticity of food. However, after trying to uncover this food authentication problem and provide a Foodomics approach, we felt the need for synergies in building a database capable of storing food matrices in the form of unique genes, bioactive peptides, and secondary metabolites. We hope that through this opinion article, the target database can be formed, although databases such as MEDLINE and PubChem have provided this data facility. In particular, we suggest the development of nanobiosensors that should undoubtedly be environmentally friendly and portable (making use of smartphones) and creating a cloud database capable of storing food matrices in the form of unique genes, bioactive peptides, and secondary metabolites, integrated with smartphone biosensors. Finally, as a result, the researcher tries to answer this database problem so that foodomics integrated with the database can solve the problem of detecting fraud and counterfeiting of foodstuffs.

Biografía del autor/a

Nurpudji Astuti Taslim, Clinical Nutrition, Faculty of Medicine, Hasanuddin University, Indonesia.

Clinical Nutrition, Faculty of Medicine, Hasanuddin University, Indonesia.

Hardinsyah Hardinsyah, Department of Applied Nutrition, IPB University, Bogor, Indonesia

  1. Department of Applied Nutrition, IPB University, Bogor, Indonesia.
  2. President, Federation of Asian Nutrition Societies, Bogor, 16680, Indonesia.
  3. President, Food and Nutrition Society of Indonesia, Bogor, West Java, 16680, Indonesia.
  4. Council Member, Southeast Asia Probiotics Scientific and Regulatory Experts Network, Petaling Jaya, Selangor, 46150, Malaysia.

Vincentius Mario Yusuf, Medical Programme, Faculty of Medicine, Brawijaya University, Malang, Indonesia

Medical Programme, Faculty of Medicine, Brawijaya University, Malang, Indonesia

William Ben Gunawan, Nutrition Science Department, Faculty of Medicine, Diponegoro University, Semarang, Indonesia

Nutrition Science Department, Faculty of Medicine, Diponegoro University, Semarang, Indonesia

Mrinal Samtiya, Department of Nutrition Biology, Central University of Haryana, Mahendragarh, India

Department of Nutrition Biology, Central University of Haryana, Mahendragarh, India

Nelly Mayulu, Faculty of Medicine, Sam Ratulangi University, Manado, Indonesia

Faculty of Medicine, Sam Ratulangi University, Manado, Indonesia

Trina Ekawati Tallei, Biology, Faculty of Mathematics and Natural Sciences, Sam Ratulangi University, Manado, Indonesia

Biology, Faculty of Mathematics and Natural Sciences, Sam Ratulangi University, Manado, Indonesia

Citas

Massaro A, Negro A, Bragolusi M, Miano B, Tata A, Suman M, et al. Oregano authentication by mid-level data fusion of chemical fingerprint signatures acquired by ambient mass spectrometry. Food Control. 2021 Aug;126:108058.

Esteki M, Regueiro J, Simal-Gándara J. Tackling Fraudsters with Global Strategies to Expose Fraud in the Food Chain. Vol. 18, Comprehensive Reviews in Food Science and Food Safety. John Wiley & Sons, Ltd; 2019. p. 425–40.

European Parliament resolution of 14 January 2014 on the food crisis, fraud in the food chain and the control thereof (2013/2091(INI)). Eur Off J. 2016;C482:22–30.

Herrero M, Simõ C, García-Cañas V, Ibáñez E, Cifuentes A. Foodomics: MS-based strategies in modern food science and nutrition. Vol. 31, Mass Spectrometry Reviews. John Wiley & Sons, Ltd; 2012. p. 49–69.

Capozzi F, Bordoni A. Foodomics: A new comprehensive approach to food and nutrition. Genes Nutr. 2013;8(1):1–4.

Balkir P, Kemahlioglu K, Yucel U. Foodomics: A new approach in food quality and safety. Vol. 108, Trends in Food Science and Technology. 2021. p. 49–57.

Valdés A, Álvarez-Rivera G, Socas-Rodríguez B, Herrero M, Ibáñez E, Cifuentes A. Foodomics: Analytical Opportunities and Challenges. Vol. 94, Analytical Chemistry. 2022. p. 366–81.

Bustamante CD, De La Vega FM, Burchard EG. Genomics for the world. Vol. 475, Nature. Nature Publishing Group; 2011. p. 163–5.

Allendorf FW, Funk WC, Aitken SN, Byrne M, Luikart G, Antunes A. Conservation and the Genomics of Populations. Conservation and the Genomics of Populations. 2022.

Seehausen O, Butlin RK, Keller I, Wagner CE, Boughman JW, Hohenlohe PA, et al. Genomics and the origin of species. Vol. 15, Nature Reviews Genetics. 2014. p. 176–92.

Van der Ryn S, Cowan S. An Introduction to Ecological Design. In: The Ecological Design and Planning Reader. 2014. p. 191–202.

Butler A, Hoffman P, Smibert P, Papalexi E, Satija R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat Biotechnol. 2018 Apr;36(5):411–20.

Satija R, Farrell JA, Gennert D, Schier AF, Regev A. Spatial reconstruction of single-cell gene expression data. Nat Biotechnol. 2015 May;33(5):495–502.

Bocklandt S, Hastie A, Cao H. Bionano Genome Mapping: High-Throughput, Ultra-Long Molecule Genome Analysis System for Precision Genome Assembly and Haploid-Resolved Structural Variation Discovery. In: Advances in Experimental Medicine and Biology. Springer New York LLC; 2019. p. 97–118.

Van Andel TR, Meyer RS, Aflitos SA, Carney JA, Veltman MA, Copetti D, et al. Tracing ancestor rice of Suriname Maroons back to its African origin. Vol. 2, Nature Plants. Nature Publishing Group; 2016. p. 1–5.

van Andel T. African rice (Oryza glaberrima Steud.): Lost crop of the enslaved Africans discovered in suriname1. Econ Bot. 2010 Mar;64(1):1–10.

Wu Q, Zhang Y, Yang Q, Yuan N, Zhang W. Review of electrochemical DNA biosensors for detecting food borne pathogens. Vol. 19, Sensors (Switzerland). Multidisciplinary Digital Publishing Institute; 2019. p. 4916.

Vetrone SA, Huarng MC, Alocilja EC. Detection of Non-PCR amplified S. enteritidis genomic DNA from food matrices using a gold-nanoparticle DNA biosensor: A proof-of-concept study. Sensors (Switzerland). 2012 Aug;12(8):10487–99.

Böhme K, Calo-Mata P, Barros-Velázquez J, Ortea I. Review of Recent DNA-Based Methods for Main Food-Authentication Topics. J Agric Food Chem. 2019 Apr;67(14):3854–64.

Li C, Zhu Y, Guo X, Sun C, Luo H, Song J, et al. Transcriptome analysis reveals ginsenosides biosynthetic genes, microRNAs and simple sequence repeats in Panax ginseng C. A. Meyer. BMC Genomics. 2013 Apr;14(1).

Wolf JBW. Principles of transcriptome analysis and gene expression quantification: An RNA-seq tutorial. Mol Ecol Resour. 2013 Jul;13(4):559–72.

Kleter GA. Food safety assessment of crops engineered with RNA interference and other methods to modulate expression of endogenous and plant pest genes. Vol. 76, Pest Management Science. John Wiley & Sons, Ltd; 2020. p. 3333–9.

Cheng YH, Liu SJ, Jiang JH. Enzyme-free electrochemical biosensor based on amplification of proximity-dependent surface hybridization chain reaction for ultrasensitive mRNA detection. Talanta. 2021 Jan;222:121536.

Su Y, Hammond MC. RNA-based fluorescent biosensors for live cell imaging of small molecules and RNAs. Vol. 63, Current Opinion in Biotechnology. Elsevier Current Trends; 2020. p. 157–66.

Li L, Zhang M, Chen W. Gold nanoparticle-based colorimetric and electrochemical sensors for the detection of illegal food additives. Vol. 28, Journal of Food and Drug Analysis. Food and Drug Administration, Taiwan; 2020. p. 641–53.

Wu Y, Dong Y, Shi Y, Yang H, Zhang J, Khan MR, et al. CRISPR-Cas12-Based Rapid Authentication of Halal Food. J Agric Food Chem. 2021 Sep;69(35):10321–8.

Aslam B, Basit M, Nisar MA, Khurshid M, Rasool MH. Proteomics: Technologies and their applications. Vol. 55, Journal of Chromatographic Science. Oxford Academic; 2017. p. 182–96.

Faria SS, Morris CFM, Silva AR, Fonseca MP, Forget P, Castro MS, et al. A Timely shift from shotgun to targeted proteomics and how it can be groundbreaking for cancer research. Front Oncol. 2017 Feb;7(FEB).

Macklin A, Khan S, Kislinger T. Recent advances in mass spectrometry based clinical proteomics: Applications to cancer research. Vol. 17, Clinical Proteomics. BioMed Central Ltd.; 2020.

Duan G, Walther D. The Roles of Post-translational Modifications in the Context of Protein Interaction Networks. PLoS Comput Biol. 2015;11(2).

Su MG, Weng JTY, Hsu JBK, Huang KY, Chi YH, Lee TY. Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions. BMC Syst Biol. 2017 Dec;11.

Wang J, Yin T, Xiao X, He D, Xue Z, Jiang X, et al. StraPep: A structure database of bioactive peptides. Database. 2018 Jan;2018(2018).

Ortea I, Cañas B, Calo-Mata P, Barros-Velázquez J, Gallardo JM. Identification of commercial prawn and shrimp species of food interest by native isoelectric focusing. Food Chem. 2010 Jul;121(2):569–74.

Artigaud S, Lavaud R, Thébault J, Jean F, Strand Ø, Strohmeier T, et al. Proteomic-based comparison between populations of the great scallop, pecten maximus. J Proteomics. 2014 Jun;105:164–73.

Fu J, Zhang Y, Wang Y, Zhang H, Liu J, Tang J, et al. Optimization of metabolomic data processing using NOREVA. Nat Protoc 2021 171. 2021 Dec;17(1):129–51.

Beisken S, Eiden M, Salek RM. Getting the right answers: Understanding metabolomics challenges. Expert Rev Mol Diagn. 2015 Jan;15(1):97–109.

reviews DW-P, 2019 undefined. Metabolomics for investigating physiological and pathophysiological processes. journals.physiology.org.

Citti C, Battisti UM, Braghiroli D, Ciccarella G, Schmid M, Vandelli MA, et al. A Metabolomic Approach Applied to a Liquid Chromatography Coupled to High-Resolution Tandem Mass Spectrometry Method (HPLC-ESI-HRMS/MS): Towards the Comprehensive Evaluation of the Chemical Composition of Cannabis Medicinal Extracts. Phytochem Anal. 2018 Mar;29(2):144–55.

Stella R, Mastrorilli E, Pretto T, Tata A, Piro R, Arcangeli G, et al. New strategies for the differentiation of fresh and frozen/thawed fish: Non-targeted metabolomics by LC-HRMS (part B). Food Control. 2022 Feb;132:108461.

Tata A, Massaro A, Riuzzi G, Lanza I, Bragolusi M, Negro A, et al. Ambient mass spectrometry for rapid authentication of milk from Alpine or lowland forage. Sci Reports 2022 121. 2022 May;12(1):1–11.

Cherng P, Wang M, Yang Y, Min J, Song Y, Tu J, et al. A wearable electrochemical biosensor for the monitoring of metabolites and nutrients. Nat Biomed Eng 2022. 2022 Aug;1–11.

Rafique B, Iqbal M, Mehmood T, Shaheen MA. Electrochemical DNA biosensors: a review. Sens Rev. 2019;39(1):34–50.

Tata A, Massaro A, Damiani T, Piro R, Dall’Asta C, Suman M. Detection of soft-refined oils in extra virgin olive oil using data fusion approaches for LC-MS, GC-IMS and FGC-Enose techniques: The winning synergy of GC-IMS and FGC-Enose. Food Control. 2022 Mar;133:108645.

Tata A, Pallante I, Zacometti C, Moressa A, Bragolusi M, Negro A, et al. Rapid, novel screening of toxicants in poison baits, and autopsy specimens by ambient mass spectrometry. Front Chem. 2022 Aug;0:983.

Zeinhom MMA, Wang Y, Song Y, Zhu MJ, Lin Y, Du D. A portable smart-phone device for rapid and sensitive detection of E. coli O157:H7 in Yoghurt and Egg. Biosens Bioelectron. 2018 Jan;99:479–85.

Lee W Il, Shrivastava S, Duy LT, Yeong Kim B, Son YM, Lee NE. A smartphone imaging-based label-free and dual-wavelength fluorescent biosensor with high sensitivity and accuracy. Biosens Bioelectron. 2017 Aug;94:643–50.

Descargas

Publicado

23-03-2023

Cómo citar

Taslim, N. A. ., Nurkolis, F., Hardinsyah, H., Yusuf, V. M. ., Gunawan, W. B. ., Samtiya, M. ., … Tallei, T. E. . (2023). Foodomics approaches to facilitate the verification of the authenticity of foods: a possible strategy to screen, validate, and standardize food matrices. Nutrición Clínica Y Dietética Hospitalaria, 43(1). https://doi.org/10.12873/431hardinsyah