BLBS102-c44 BLBS102-Simpson March 21, 2012 14:34 Trim: 276mm X 219mm Printer Name: Yet to Come
848 Part 8: Food Safety and Food Allergensafter passing through a sample, the data collected is analyzed
using Fourier transformation and the resulting output results in
a spectrum identical to the conventional infrared spectroscopy.
FTIR has been used to differentiate and quantifySalmonella,
E. coliO157:H7, andListeriain various media or substrates
(Lin et al. 2004, Yu et al. 2004, Al-Holy et al. 2006). Ellis et al.
(2002) reported the use of FTIR directly on food to detect unique
biochemical fingerprints of pathogens and provided a measure
of bacterial loads.Surface Plasmon ResonanceSurface plasmon resonance (SPR) uses reflectance spectroscopy
to detect pathogens. The principle of the technique is based on
the technology being able to detect minor changes in refrac-
tive index, which occur as cells of the target bind to receptors
immobilized on a transducer surface. Changes in the angle of
reflected light are measured as a function of changes in density
of the medium versus time. SPR sensors have been used by a
number of researchers for the detection of a range of pathogens
includingL. monocytogenes,Salmonella,E. coliO157:H7, and
C. jejuni(Koubova et al. 2001, Bokken et al. 2003, Bhunia et al.
2004, Leonard et al. 2004, Meeusen et al. 2005, Subramanian
et al. 2006, Taylor et al. 2006, Waswa et al. 2007).
SPR technologies use antibodies that are immobilized on a
gold electrode surface that can measure miniscule changes in
resonance frequency as a result of antibody antigen binding oc-
curring (Feng 2007). Su and Li (2004) incorporated SPR with a
piezoelectric system for the detection ofE. coliO157:H7 at lev-
els ranging from 10^3 to 10^8 cells; a similar approach by Oh et al.
(2004) could detectS. typhimuriumat levels ranging from 10^2
to 10^9 CFU/mL and Leonard et al. (2004, 2005) report detection
of 10^5 cells/mL ofL. monocytogenesin less than 30 minutes.
Oh et al. (2004) report the development of an SPR chip capa-
ble of detecting multiple organisms simultaneously including
E. coliO157:H7,S. typhimurium,Legionella pneumophila, and
Yersinia enterocolitica.Mass Sensitive BiosensorsMass sensitive biosensors work on the principle of detection of
minute changes in mass. The analysis depends on the use of
piezoelectric crystals that vibrate at a specific frequency, as a
result of electrical input at the same frequency. The frequency
depends on electrical input and the mass of the crystal. If the
mass of the crystal increases due to binding of agents, the weight
of the crystal will change and therefore the oscillation frequency.
The difference in oscillation results in a change, which can be
measured electronically. Quartz is one of the most common
piezoelectric material and the main types of sensors are quartz
crystal microbalance (QCM) or surface acoustic wave (SAW).
When the surface of the sensor is coated with an antibody and
exposed to liquid containing the target pathogen—the pathogens
will bind to the antibody resulting in a change in the weight of the
crystal, and a shift in its frequency oscillation. QCM have been
used in the detection ofSalmonella(Su and Li 2005),L. monocy-
togenes(Vaughn et al. 2001), andE. coliO157:H7 (Berkenpaset al. 2006). Modifications of the microbalance principle in-
clude piezoelectric excited millimeter sized cantilever and mag-
netoelastic sensors (Ruan et al. 2004, Mutharasan and Campbell
2008).Electronic Nose SensorsElectronic nose technology for pathogen detection works on the
principle of detection of volatiles produced by active organisms
in a food sample. The system is based on adsorption of volatiles
to a series of conducting organic polymers; once the volatiles are
adsorbed there is a change in the resistance of the sensors that
can be equated to the presence of an organism or a population
of organisms. Balasubramanian et al. (2005) used a commercial
electronic nose system to detectSalmonellain inoculated beef
samples. The system was able to differentiateSalmonellacon-
taminated from noncontaminated meat. Similar systems have
also been used in the detection ofE. coliO157:H7 Younts et al.
(2002, 2003) assessed the use of gas sensors for detection of
E. coliO157 and non-O157 strains. Sensitivity and specificity
ranged from 41.7 to 50% for nonnormalized data, which con-
trasted to data normalized using artificial neural network (ANN)
classification that increased sensitivity from 91.7% to 100% but
specificity ranged from 37.5% to 50%. Magan et al. (2001) used
a commercial system for detection ofPseudomonasandBacillus
species in milk; Muhamed-Tahir and Alocilja (2003) developed
a portable sensor system for detection ofE. coliO157:H7 with
a minimum detection limit of 7.8× 101 CFU/mL. Arshak et al.
(2009) used a series of conducting polymers to detect a range
of food-borne pathogens includingSalmonella,Bacillus cereus
andVibrio parahaemolyticus, and was able to differentiate each
based on its signal.Nanotechnology for Pathogen DetectionAs one of the latest technologies, nanotechnology presents a
great opportunity for rapid detection, diagnosis, and identifica-
tion of pathogens. Nanoparticles, in particular, gold and silver
have electronic and optical properties that make them useful
in next generation detection. When the particles are coupled to
affinity ligands they can be useful in pathogen detection; for ex-
ample, gold nanoparticles coupled with specific oligonucleotides
can detect complementary DNA. Other types of nanoparticles
including quantum dots and carbon nanotubes have been used
in assays for detection of pathogens, toxins, DNA, and in im-
munoassay development (Kaittanis et al. 2010). Recent arti-
cles by Kaittanis et al. (2010) and Tallury et al. (2010) provide
some interesting overviews of nanotechnology applications in
pathogen detection.SUMMARY
Pathogens associated with human disease are constantly chang-
ing, what was old is now new and what was new has emerged in
new ways not previously recognized as a means to cause disease.
As fast as the pathogens are emerging, technologies and appli-
cations for their detection have become the next race to find the