Assessment of Genetically Modifi ed Organisms (GMO) in Meat Products by PCR 513protocol based on highly sensitive PCR
methodologies.High Throughput Detection.
The methodology for reliable GMO detec-
tion, based on real - time PCR, is rather well
established under laboratory conditions. This
validated technology needs to be compliant
with EU mandatory rules governing the
labeling of food products with over 0.9% of
authorized GMO (European Commission
2003b ). However, two practical limitations
offer hurdles to its adjustment to the expected
growing requirements: the number of GMO
authorizations is expected to increase in the
future (Golden Rice will be available for
farmers in 2011), and subsequently, the
number of agronomical traits and transgene
events should parallel such an increment; and
the economical cost for GM food analysis,
based on real - time PCR methods, is still far
from being affordable due to the large number
of samples to be analyzed in the future.
A promising approach that could bypass
both limitations is the application of microar-
ray technology, which enables the simultane-
ous detection of a large number of different
targets (Elenis et al. 2008 ). The development
of colorimetric - based detection methods in
the microarray system would also help reduce
the cost of expensive current fl uorescent
methodologies for detection. In spite of its
great potential to become the standard GMO
detection methodology, microarray technol-
ogy suffers a severe restriction related to the
needs of effi cient quantifi cation as required
for GMO labeling, which may hamper its
apparent superiority. The possible solution to
this drawback is to perform quantitative
amplifi cation and detection after hybridiza-
tion on the chip, which could be achieved
with available techniques.
Some microarray - based methods have
already been developed. Germini et al. (2005)
developed a PNA microarray for the detec-
tion of four GM maizes, one GM soybean,356043 and 305423 soybean, Bt11 event
176, CBH - 351, GA21, NK - 603, MON810
MON863xMON810, 1507, 3272, MIR604,
59122 maize lines, EH92 - 527 - 1 potato, 281 -
24 - 236 x 3006 - 210 - 23 cotton seed, and
H7 - 1 sugar beet ( http://irmm.jrc.ec.europa.
eu/html/reference_materials_catalogue/cata-
logue/RM_Catalogue.pdf ).
Finally, the selection of the analytical
method to be used must consider three prem-
ises: (1) the scientifi c knowledge in the fi eld;
(2) the principal performance features of the
available methodologies (e.g., specifi city,
sensitivity, accuracy, and precision); and (3)
practical aspects, such as cost per analysis,
time to achieve conclusive results, and ease
of sample handling and processing (Auer
2003 ). The CRL publish validated methods
for detection of authorized GMOs ( http://
gmo-crl.jrc.ec.europa.eu/statusofdoss.htm ).
During recent years, molecular approaches
have signifi cantly contributed to the fi eld of
GMO detection. However there are several
limitations that prevent the total implementa-
tion of these methodologies into food labora-
tories. The major inconvenience is the cost
of the required devices and reagents, and
the need for qualifi ed personnel. Even though
the demand for RTi - PCR instruments has
constantly decreased in recent years with a
parallel decline in their cost, the expense -
per - analysis is still too high to be practical
for routine analysis in food laboratories.
Other potential problems facing the imple-
mentation of molecular - based methodologies
include the risk of contamination and the
diffi culties in the extraction process of certain
types of food sample. As instrumental tech-
niques, the molecular - based methods have
a tendency to produce false - negative and
- positive results. The main cause of false -
positive results is the accidental contamina-
tion of the samples or the reagents with
positive samples (cross contamination) and
with amplifi cation products and plasmid
clones (carry - over contamination). This is
a central issue for any GMO - detection