Foodomics

(Redirected from Foodome)

Foodomics was defined in 2009 as "a discipline that studies the Food and Nutrition domains through the application and integration of advanced -omics technologies to improve consumer's well-being, health, and knowledge".[1] Foodomics requires the combination of food chemistry, biological sciences, and data analysis.

Genetically engineered animals

The study of foodomics became under the spotlight after it was introduced in the first international conference in 2009 at Cesena, Italy. Many experts in the field of omics and nutrition were invited to this event in order to find the new approach and possibility in the area of food science and technology. However, research and development of foodomics today are still limited due to high throughput analysis required. The American Chemical Society journal called Analytical Chemistry dedicated its cover to foodomics in December 2012.[2]

Foodomics involves four main areas of omics:[3]

  • Genomics, which involves investigation of genome and its pattern.[citation needed]
  • Transcriptomics, which explores a set of gene and identifies the difference among various conditions, organisms, and circumstance, by using several techniques including microarray analysis;[citation needed]
  • Proteomics, studies every kind of proteins that is a product of the genes. It covers how protein functions in a particular place, structures, interactions with other proteins, etc.;[4]
  • Metabolomics, includes chemical diversity in the cells and how it affects cell behavior;[5]

Advantages of foodomics

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Foodomics greatly helps the scientists in an area of food science and nutrition to gain a better access to data, which is used to analyze the effects of food on human health, etc. It is believed to be another step towards better understanding of development and application of technology and food. Moreover, the study of foodomics leads to other omics sub-disciplines, including nutrigenomics which is the integration of the study of nutrition, gene and omics.

 
Rosemary

Colon cancer

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Foodomics approach is used to analyze and establish the links between several substances presented in rosemary and the ability to cure colon cancer cells. There are thousands of chemical compounds in rosemary, but the ones that are able to help cure such disease are Carnosic acid (CA) and Carnosol (CS), which can be obtained by extracting rosemary via SFE. They have the potential to fight against and reduce the proliferation of human HT-29 colon cancer cells.[6]

The experiment done by inserting rosemary extracts to the mice and collecting RNA and metabolites from each controlled and treated individual indicated that there is a correlation between the compounds used and the percentage of recovery from the cancer. This information is however never achievable without the help of foodomics knowledge as it was used to process data, analyze statistic, and identify biomarkers. Foodomics, coupled with transcriptomic data, shows that Carnosic acid leads to the accumulation of an antioxidant, glutothione (GSH). The chemical can be broken down to Cysteinylglycine, a naturally occurring dipeptide and an intermediate in the gamma glutamyl cycle. Moreover, the result from an integration of foodomics, transcriptomics and metabolomics reveals that provoking colon cancer cell compounds, such as N‐acetylputrescine, N‐acetylcadaverine, 5’MTA and γ‐aminobutyric acid, can also be lowered by CA treatment.[6]

Thus, foodomics plays an important role in explaining the relationship between deadly disease, like colon cancer, and natural compounds existing in rosemary. Data obtained is useful in reaching another approach for tackling proliferation against cancer cells.[7][8]

Processed meat

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Aside from measuring the concentration of protein in meat, calculating bioavailability is another way in determining the total amount of component and quality. The calculation is done when food molecules are digested in various steps. Since human digestion is very complicated, a wide range of analytical techniques are used to obtain the data, including foodomics protocol and an in vitro static simulation of digestion.[9]

 
Bresaola or the air-dried and salted beef. It is made from a single muscle of beef.

The procedure is divided into 3 stages as the samples are collected from oral, gastric and duodenal digestion in order to study protein digestibility closely and thoroughly. A meat based food, Bresaola, is evaluated because beef muscles are still intact, which can be used to indicate nutritional value.[9]

The consequences of oral step can be observed at the beginning of the gastric digestion, the first stage. As there is no enzymatic proteolytic activity at this stage, the level of H-NMR, a spectrum used to determine the structure, is still constant because there is no change going on. However, when pepsin takes action, TD-NMR, a special technique used for measuring mobile water population with macromolecular solutes, reveals that progressive unbundling of meat fibers helps pepsin activity to digest. TD-NMR data proves that bolus structure changes considerably during the first part of digestion and water molecules, consequently, leave the spaces inside the myofibrils and fiber bundles. This results in a low level of water that can be detected in duodenal stage. Since digestion is in progress, protein molecules become smaller and molecular weight gets lower, in other words, there is an increase in the spectra total area.[9]

See also

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References

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  1. ^ Cifuentes, Alejandro (23 October 2009). "Food analysis and Foodomics". J. Chromatogr. A. 1216 (43): 7109. doi:10.1016/j.chroma.2009.09.018. hdl:10261/154212. PMID 19765718.
  2. ^ García-Cañas, Virginia; Simó, Carolina; Herrero, Miguel; Ibáñez, Elena; Cifuentes, Alejandro (4 December 2012). "Present and Future Challenges in Food Analysis: Foodomics". Analytical Chemistry. 84 (23): 10150–10159. doi:10.1021/ac301680q. hdl:10261/101428. PMID 22958185.
  3. ^ Capozzi, Francesco; Bordoni, Alessandra (January 2013). "Foodomics: a new comprehensive approach to food and nutrition". Genes & Nutrition. 8 (1): 1–4. doi:10.1007/s12263-012-0310-x. PMC 3535000. PMID 22933238.
  4. ^ Graves, Paul (1 March 2002). "Molecular Biologist's Guide to Proteomics". Microbiology and Molecular Biology Reviews. 66 (1): 39–63, table of contents. doi:10.1128/MMBR.66.1.39-63.2002. PMC 120780. PMID 11875127.
  5. ^ Clish, Clary (1 October 2015). "Metabolomics: an emerging but powerful tool for precision medicine". Cold Spring Harbor Molecular Case Studies. 1 (1): a000588. doi:10.1101/mcs.a000588. PMC 4850886. PMID 27148576.
  6. ^ a b Cifuentes, Alejandro (May 2015). "Foodomics: Food Science & Omics Tools in the 21st Century" (PDF). NMKL - Nordval International. Archived from the original (PDF) on 2017-05-16.
  7. ^ Ballesteros-Vivas, Diego; Alvarez-Rivera, Gerardo; León, Carlos; Morantes, Sandra Johanna; Ibánez, Elena; Parada-Alfonso, Fabián; Cifuentes, Alejandro; Valdés, Alberto (April 2020). "Foodomics evaluation of the anti-proliferative potential of Passiflora mollissima seeds". Food Research International. 130: 108938. doi:10.1016/j.foodres.2019.108938. PMID 32156385. S2CID 212666224.
  8. ^ Ballesteros-Vivas, Diego; Alvarez-Rivera, Gerardo; León, Carlos; Morantes, Sandra Johanna; Ibánez, Elena; Parada-Alfonso, Fabián; Cifuentes, Alejandro; Valdés, Alberto (December 2019). "Anti-proliferative bioactivity against HT-29 colon cancer cells of a withanolides-rich extract from golden berry (Physalis peruviana L.) calyx investigated by Foodomics". Journal of Functional Foods. 63: 103567. doi:10.1016/j.jff.2019.103567. hdl:10261/204591. S2CID 203881293.
  9. ^ a b c Bordoni, Alessandra; Laghi, Luca; Babini, Elena; Nunzio, Mattia Di; Picone, Gianfranco; Ciampa, Alessandra; Valli, Veronica; Danesi, Francesca; Capozzi1, Francesco (5 March 2014). "The foodomics approach for the evaluation of protein bioaccessibility in processed meat upon in vitro digestion". Electrophoresis. 35 (11): 1607–1614. doi:10.1002/elps.201300579. PMID 24436037. S2CID 39219807.{{cite journal}}: CS1 maint: numeric names: authors list (link)