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Open AccessEditorial
Data Mining in Genomics & Proteomics
Josic and Giacometti, J Data Mining Genomics Proteomics 2013, 4:2
http://dx.doi.org/10.4172/2153-0602.1000e106
Volume 4 • Issue 2 • 1000e106
J Data Mining Genomics Proteomics
ISSN: 2153-0602 JDMGP, an open access journal
Introduction
Aer rather slow beginning, the “omics” methods are gaining in
importance for process development and validation in food technology
and biotechnology as well as corresponding quality control of starting
materials and nal products [1]. is methodology is increasingly used
for analyses of food composition and quality, food authentication,
safety assessment of genetically modied food, identication of food
allergens, presence of toxins, analysis of the physiological activity
of food proteins and peptides, and the inuence of the production
process on the chemical, physicochemical and biological properties of
food proteins [2], and a specic term “foodomics” was also recently
coined. e number of papers dealing with use of omics methods in
food processing and nutrition has also rapidly increased, especially
on the eld of food of animal origin [3]. Advances in whole genome
sequencing of plants that are important for human nutrition have
also removed the major obstacle for the use of foodomic, especially
proteomic methods for food of plant origin [1]. Furthermore, organic
food of both plant and animal origin plays an increasingly important
role in the food market, therefore foodomic methods are used for the
identication and quality assurance of organic food, and discovery
of potential fake organic products [4]. Similar to the organic food,
the traditional fermented food is again gaining in popularity. In this
kind of food of both animal and plant origin such as meat, milk and
milk products, wine, beer and other fermented products, changes of
the proteome of the substrate (e.g. sausages, fermented milk products
and grape juice) and in the starter culture microorganisms (e.g. milk
bacteria, bacterial and mixed microora in fermented meat product,
and yeasts in both wine and beer) as well as their interaction play a
crucial role in the quality of the nal products [4]. Fermentation also
means enzymatic digestion of food components, and accumulation of
small molecules in the nal product. ese molecules are frequently
responsible for specic avor of original fermented food and can be
used as markers for its originality and identity [5]. On the other hand,
in production of both organic and traditional fermented food, thermal
and other steps for microbial inactivation and inactivation of toxins
and allergens are frequently avoided. It is the reason that this kind
of food can get a serious safety risk, especially if contaminated raw
materials are used or improperly prepared.
Foodomics-Towards the Integrated Omics in Food
Science
At this moment, foodomics constitute one of the most relevant
and fast developing areas in food science. Slowly, but constantly, the
formerly fully independent worlds of the experts in food technology
and microbiology, nutrition, genomics, proteomics (together with
glycomics, phosphoproteomics and other methods dealing with
posttranslational modication of proteins) and metabolomics have
started to interact. e aim of this cooperation is to ameliorate the
food quality and safety, and to prevent food adulteration. e rights of
consumers and genuine food processors in terms of food adulteration
and fraudulent or deceptive practices in food processing are set out in
the European Union regulations regarding food safety and traceability.
is system was developed in order to: (i) encourage diverse
agricultural production; (ii) protect product names from misuse and
imitation; (iii) help consumers by giving them information concerning
the specic character of the product [6]. e potential use of foodomics
in their development pathway for food production, assessing the safety,
originality and quality is shown in gure 1.
As soon as the above mentioned collaboration was intensied,
it clearly emerged that the integration of all foodomics disciplines
will represent a more suitable tool than each discipline by itself, e.g.,
proteomics or genomics alone. e result was an intensive collaboration
between the experts on dierent elds of food science and nutrition
and omics experts. e use of foodomics enabled, or at least facilitated
the answers to the questions that are crucial for food safety, quality,
traceability and its protection against adulteration. ese points are:
(i) geographical origin (ii) handling (iii) quality and originality of the
starting material (iv) use of genetically modied food and/or transgenic
microbial cultures (v) use of antibiotics, fungicides and herbicides
during animal and crop cultivation (vi) microbial contamination
during the production process, handling and storage [7].
*Corresponding author: Djuro Josic, Warren Alpert Medical School, Brown
University, Providence, USA, E-mail: djuro_josic@brown.edu
Received March 01, 2013; Accepted March 04, 2013; Published March 11, 2013
Citation: Josic D, Giacometti J (2013) Foodomics-Use of Integrated Omics
in Nutrition, Food Technology and Biotechnology. J Data Mining Genomics
Proteomics 4: e106. doi:10.4172/2153-0602.1000e106
Copyright: © 2013 Josic D, et al. This is an open-access article distributed under
the terms of the Creative Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the original author and
source are credited.
Foodomics-Use of Integrated Omics in Nutrition, Food Technology and
Biotechnology
Djuro Josic1,2* and Jasminka Giacometti2
1Warren Alpert Medical School, Brown University, Providence, USA
2Department of Biotechnology, University of Rijeka, Rijeka, Croatia
Quality control
Quality control
Microbial control
In process control
Raw material
(plant or animal origin)
Food processing
Final products
Cleaning and sanitation
Production process,food safety and quality
Microbial and biological safety
Production steps
Analysis of food components
Safety
Batch-to-batch variations
Detection of resistent microorganisma
Proteomics - microbial proteomics
Proteomics
Proteomics
Proteomics
Protein interactions
Protein interactions
Protein changes
Protein changes
Protein changes
Contaminants
Contaminants
Contaminants
Figure 1: Use of foodomics in the development pathway for food production,
and assessing food safety, originality and quality [7].
Citation: Josic D, Giacometti J (2013) Foodomics-Use of Integrated Omics in Nutrition, Food Technology and Biotechnology. J Data Mining Genomics
Proteomics 4: e106. doi:10.4172/2153-0602.1000e106
Page 2 of 3
Volume 4 • Issue 2 • 1000e106
J Data Mining Genomics Proteomics
ISSN: 2153-0602 JDMGP, an open access journal
High-throughput Methods
Both the sampling and the high-throughput sample preparation are
the rst critical point in foodomic analyses. ey are critical for both
exact and very fast analytical work. Optimization of sample preparation,
extraction and parallel chromatographic separation of extracts before
further analysis by use of robotics is the rst step on the way for fast and
exact omics food analyses. e use of miniaturized columns packed
with bulk supports or containing monoliths for parallel separation
of 96 samples was already introduced [8]. Dierent chromatographic
supports can be used for stepwise separation of complex biological
mixtures before further proteomic and metabolomic analyses.
Already three years ago, we emphasized that most proteomic
analyses of food components are based on protein separation
by gel electrophoresis [7]. In proteomic analysis of food, the 2D
electrophoresis is still the most used method for protein separation
before their identication by LC-MS/MS [1]. Although this method
provides very high resolution and eective separation of very similar
components, it is time-consuming and the use of robotics for high-
throughput sampling is dicult. e use of gel-free proteomics enables
the sample preparation and high-throughput analysis of samples, as
well as integration of other parallel omics methods, e.g., determination
of metabolites in the same analytical run. For quantitative analyses, gel-
free, label-free methods with application of the corresponding soware
will be introduced. New soware can be used for direct comparison of
samples at both protein (proteomics), peptide and other low molecular
weight components (peptidomic, metabolomic) level in order to
determine dierently expressed components on the further way of
determination of possible candidates and validation of (bio) marker
candidates [7].
Development of Methods for Determination of Food
Quality and Originality
In order to determine the discrimination of fresh versus frozen
meat (http://www.spiegel.de/spiegel/print/d-81562346.html, Der
Spiegel online), several foodomic methods can be used such as
DNA based techniques, spectroscopy (including the NMR), sensory
methods and bio imaging. Omics methods are also gaining importance
for determination of the used antibiotics in meat production, use
of growth promoter abuse by metabolomic or proteomic methods
[1,7], adulteration of raw materials in production of high-value food
[9,10], and in order to determine the speed of the spoilage of raw
material [11]. It was already demonstrated that previous, very eective
methods for food analysis and detection of adulterations can be further
optimized by introduction of new, rapid and more sensitive methods
at the higher level of the present state-of-the art [9,12]. Important
contribution will be the application of so-called “activomics”. It is
the method that is following the change of enzyme activities in target
samples (e.g., dierent proteases or kinases) by use of MALDI-TOF
mass spectrometry. In combination with other methods, activomics
can explore the changes in the food during storage (e.g., freezing, or
freezing/thawing) as well as during the production process, or changes
caused by microbial contamination.
Russo et al. [12] demonstrated that the adulteration by replacement
of bualo by bovine milk can be detected by analyses of post-translation
modications, in this case, casein phosphopeptides. Introduction of
this methodology will be also be very useful for (phospho) proteomic
and genomic meat analysis [13].
With few exceptions, glycomic and phosphoproteomic analyses in
foodomics are now limited to milk [7]. Analyses of changes of post-
translational modications, primarly glycosylation and phosporylation
will be applied in order to determine the quality and originality of the
starting materials following the changes during food fermentation,
as well as typical pattern related to food adulterations. Additional
information will be gained by parallel investigation of phospholipids’
changes [14].
Imaging mass spectrometry is further method for determination
of the distribution of small molecules and small and middle sized
proteins in complex biological samples. is method was mostly used
in medicine for discovery of disease biomarkers [15] which can be
adapted for use in food analysis.
e eld of foodomic disciplines is a rapidly evolving scenario
lled with the technological innovations (high-throughput sample
preparation, optimized LC and MS instruments), bioinformatics tools
(e.g., in direction of the label-free quantitative MS analysis) and other
practical issues in this eld. e coordination of the collaboration of all
participating groups will nally result in an integration of all applied
omic disciplines converging to the eld of foodomics and it will
represent more suitable tool than each discipline alone in providing
the answers that are addressed above.
References
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Citation: Josic D, Giacometti J (2013) Foodomics-Use of Integrated Omics in Nutrition, Food Technology and Biotechnology. J Data Mining Genomics
Proteomics 4: e106. doi:10.4172/2153-0602.1000e106
Page 3 of 3
Volume 4 • Issue 2 • 1000e106
J Data Mining Genomics Proteomics
ISSN: 2153-0602 JDMGP, an open access journal
14. Wang Y, Zhang H (2011) Tracking phospholipid proling of muscle from
Ctenopharuyngodon idellus during storage by shotgun lipidomics. J Agric Food
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Citation: Josic D, Giacometti J (2013) Foodomics-Use of Integrated Omics
in Nutrition, Food Technology and Biotechnology. J Data Mining Genomics
Proteomics 4: e106. doi:10.4172/2153-0602.1000e106
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