5 - recent trends in molecular techniques for food

177Chemical Analysis of Food. http://dx.doi.org/10.1016/B978-0-12-813266-1.00005-XCopyright © 2020 Elsevier Inc. All rights reserved.

5

1 IntroductionMolecular detection techniques have continued to grow from

simple DNA-based gel electrophoresis to polymerase chain reac-tion (PCR) to now next-generation sequencing (NGS)-based methods. These methods are increasingly shown to have implica-tions in clinical microbiology laboratories for various purposes to add to accuracy, precision, ease, and speed to a detection method. Recent developments in molecular techniques have shown rays of hope to clinical microbiology, which is known to face challenges imposed due to restrictions of existing diagnostic methods and rising population, bioterrorism, antibiotic resistance, change in climate and trade. With availability of more and more regulations and guidelines issued by European Commission (EC), Food and Drug Administration (FDA) and Hazard Analysis Critical Control Point (HACCP) molecular applications in the diagnosis of infec-tious diseases have become common place in academic medical centers and tertiary care facilities. Therefore, it is also a known fact that quality and safety assurance are considered among most important issues in food quality control. Monitoring presence of unwanted elements (toxins/hazardous materials) or unfavorable microorganisms such as bacteria, viruses, yeast, and molds at dif-ferent stages of food production prior to its consumption is inte-gral part of food industry.

Contemporary and conventional methods of microbial diag-nosis rely on specific microbiological and biochemical iden-tification techniques. These are basically culture dependent

Recent trends in molecular techniques for food pathogen detectionSakshi Raoa, Kavita Arorab

aPersistent Systems Ltd., Pune, Maharashtra, India; bAdvanced Instrumentation Research Facility and School of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi, India

178 Chapter 5 Recent trends in molecular techniques for food pathogen detection

techniques that start from isolation, purification, and identifica-tion of microbes, preparation of different types of culture media, culturing, subculturing, pure culture maintenance, and staining techniques followed by biochemical characterization/assays, etc. These methods are limiting to practical requirements as among all the microbes only 1% of them can be cultured in the laboratory and require multiple tests for identification. Misidentification may also result due to the presence of identical probe target sequences in phylogenetically diverse organisms (Giraffa & Carminati, 2008). Moreover, these conventional methods are not particularly suited to laboratory environment due to requirement of skilled man-power, excessive external reagents, complicated sample prepa-ration methods and time-consuming procedures, etc. One of the proficiency testing program in food microbiology named RAEMA (Reseau d’Analyses et d’Echanges en Microbiologie des Aliments, created in 1988, included 450 participating laboratories) that cited assessment of interlaboratory comparison to estab-lishes proficiency in different culture-based detection methods for Salmonella, Listeria monocytogenes, enumeration of aerobic microorganisms, Enterobacteriaceae, coliforms, b-glucuronidase-positive Escherichia coli, anaerobic sulfite-reducing bacteria, Clostridium perfringens, coagulase-positive staphylococci, etc. (Augustin & Carlier, 2006) It was concluded that with the increase in complications of experimental procedure, type of microbe and food matrix, standard deviation in proficiency testing also increases due to associated repeatability and reproducibility requirements.

To cope up with the rising needs for performance-oriented methods and to screen multiple samples in one go (Crutchfield, Kuchler, & Variyam, 1999; Leonard, 2003), newer molecular meth-ods are appearing as promising and preferred mode of detection. These molecular components (nucleic acids) help avoiding steps of isolating and culturing the organism (or its single components). The unique DNA sequences are suitable to provide specific bio-logical information at taxonomic level. Besides this, recent developments in molecular tools and technologies have allowed drawing information from food samples in an easy and reliable way—right from basic polymerase chain reaction (PCR) to digital PCR, printed microarrays to high-throughput variation detection microarrays and next-generation sequencing (NGS). This chapter is an attempt to describe various basic and emerging molecular techniques for application toward detection of foodborne patho-gens and genetically modified organisms (GMOs) in food with major focus toward recent developments of PCR, microarrays, and next-generation sequencing.

Chapter 5 Recent trends in molecular techniques for food pathogen detection 179

2 Nucleic acids: the backbone of all molecular techniques

Nucleic acids are known to play a vital role in cell functioning and are called “molecule of life” among all other major macromol-ecules like protein, carbohydrates, and lipids. Nucleic acids have contributed toward development of various molecular techniques for detection of food-borne pathogens. Friedrich Miescher was the first one who discovered nucleic acids in 1871. A nucleic acid is a polymeric macromolecule made up of repeated units of mono-meric “nucleotides” composed of a nitrogenous heterocyclic base which is either a purine or a pyrimidine, a pentose (five carbon) sugar (either ribose or 2′-deoxyribose), and one to three phos-phate groups. Together, the nitrogenous base and sugar comprise a “nucleoside.” The phosphate group forms bond with the 2′, 3′, or 5′-carbon (Fig. 5.1) of the sugar (either ribose or deoxyribose) constituting a nucleotide (either ribonucleotide or deoxyribo-nucleotide, respectively). Nucleotides can contain either a purine [adenine (A) and guanine (G)] or a pyrimidine [cytosine (C), thy-mine (T) and uracil (U)] base where T is found only in DNA and U in RNA.

Nucleic acid generally consists of a single-stranded (ss) nucleo-tide chain having sugars and phosphates connected to each other by shared oxygen forming “phosphodiester bond.” The phosphate groups are attached to 5′ and 3′ carbon of the sugar giving polarity to nucleic acids and the bases extend from a glycosidic linkage to the 1′ carbon of the pentose sugar ring. Bases are joined through N-1 of pyrimidines and N-9 of purines to 1′ carbon of ribose/deoxyribose through N-β glycosidic bond. In DNA, two single-stranded nucleic acid chains of opposite polarity (3′ to 5′ and 5′ to 3′ carbon of the sugar-phosphate back bone) are held together by hydrogen bonds formed between the complementary nitro-gen bases (A with T though double hydrogen bonds and G with C through three hydrogen bonds) forming double-stranded (ds)

Figure 5.1. A typical structure of nucleoside, nucleotide, and nitrogenous bases.


DNA helix. RNA is usually single-stranded, with its strand folded back upon itself to form secondary structure (e.g., tRNA, rRNA).

2.1 RNARibonucleic acid, or RNA, is named on the bases of ribose sugar

group found in backbone. In 1953, Alexander Rich with famed chemist Linus Pauling discovered the structure of RNA at Caltech using X-ray crystallography. RNA is a single-stranded nucleotide chain containing the adenine (A), cytosine (C), uracil (U), and gua-nine (G) bases. RNA is known to be involved in several important roles like transcribing genetic information from deoxyribonucleic acid (DNA) into proteins. RNA acts as a messenger between DNA and protein synthesis through complexes known as ribosomes, forms vital portions of ribosomes, and serves as an essential car-rier molecule for amino acids to be used in protein synthesis. Three types of RNA include tRNA (transfer), mRNA (messenger), and rRNA (ribosomal). RNA is usually single-stranded, but any given strand may fold back upon itself to form secondary struc-ture (i.e., tRNA and rRNA).

2.2 DNAJames Watson and Francis Crick with Maurice Wilkins and

Rosalind Franklin, on the basis of X-ray crystallographic studies, determined the true structure of DNA in 1953. In 1962, Watson and Crick along with Maurice Wilkins received the Nobel Prize for Medicine for their most considerable contribution to the field of science. The information in DNA is stored as a code made up of four heterocyclic chemical bases: adenine (A), guanine (G), cyto-sine (C), and thymine (T). According to Chargaff’s rule, DNA bases pair up with each other, A=T (two hydrogen bonds) and C Ξ G (three hydrogen bonds), to form units called base pairs and there-fore the number of A = T, and G = C, Fig. 5.2.

DNA being a versatile molecule that possesses interesting phys-icochemical features that have implications in food-borne patho-gen detection. DNA is a stable molecule at high temperatures, and it is uniformly distributed in different tissues of an organism. Besides this, unique properties of DNA have made it the backbone for various molecular techniques. First, it can make exact copies of itself, through a process called “Replication” (Fig. 5.3). Replication is a process wherein two strands of double helix separate and a new partner is synthesized to exactly match each parent half by the action of polymerase enzyme. Second, with the change in tem-perature or pH, two strands of the DNA double helix can be dena-tured (separated or unfolded) and renatured (annealed) upon


Figure 5.2. DNA double helical structure.

Figure 5.3. DNA replication.


bringing the conditions slowly back to normal. Most of molecu-lar techniques have been developed exploiting these unique fea-tures of nucleic acids. PCR is among one of the most important techniques that involves denaturation of the target DNA at high temperature and a complimentary copy of target sequence is syn-thesized in presence of a thermo-stable polymerase enzyme via use of thermal cycles.

3 Recent molecular techniques for detection of food borne pathogen3.1 Polymerase chain reaction

Polymerase chain reaction (PCR) is most common and pow-erful molecular technique used in variety of biological research or analytical applications. As mentioned earlier, Kary Mullis in 1983 introduced this technique and was awarded the Nobel Prize in Chemistry. Low numbers of foodborne pathogen present in desired samples could be very easily detected using PCR. Basic PCR carries out exponential amplification/synthesis of comple-mentary DNA sequence from a single or few copies of DNA to several million folds within a short span of time using process of thermal cycling. This was realized through availability of auto-mated thermocyclers and thermostable polymerases in a process of repetitive heating–cooling cycles for denaturation, synthesis, and renaturation of the target strand. Amplification is achieved by annealing of specific primers (short DNA fragments) complemen-tary to the terminal region of target strand followed by enzymatic replication of the DNA with a thermostable polymerase enzyme (Chien, Edgar, & Trela, 1976) in presence of deoxynucleotide tri-phosphates (dNTPs). Each amplification cycle produces a com-plementary DNA strand to the target gene. A typical PCR reaction (Table 5.1) consists of template DNA, a pair of primers, MgCl

2,

deoxynucleotide triphosphates (dNTPs) and a thermostable DNA polymerase in ‘reaction mixture’. Each PCR cycle consists of the following steps (Fig. 5.4):

Step I. Denaturation: This is the first step of the thermal cycle that involves disruption of the hydrogen bonds (denaturation) between complementary bases, yielding single-stranded template DNA onto which primers will anneal. This step of denaturation or melting of DNA is carried out at 90–94°C.

Step II. Annealing: This step involves the hydrogen bond for-mation between primers and their complementary sequences present on single-stranded DNA template at 50–65°C. Stable DNA–DNA hydrogen bonds are only formed when the primer


Table 5.1 A typical PCR reaction mixture.

Name of the constituent

Desired concentration for 1× reaction mixture Purpose

Water – To make up the volume of the reaction mixture to get desired concentration of each constituent and facilitate the synthesis process.

Buffer and cosolvents

1X To maintain desired pH of the master mix. It is chosen with reference to the target sequence as cosolvents may be added to these standard buffers (like DMSO, betaine, formamide, or glycerol when trying to amplify G + C rich target or through regions of strong secondary structure).

Deoxynucleotide Triphosphates

200 µM To provide both the energy and nucleotides for the synthesis of DNA. It is important to add equal amounts of each nucleotide (dATP, dTTP, dCTP, dGTP) to the master mix to prevent mismatches of bases. Modified dNTPs (dig-11-dUTP, 5-bromo-dUTP, inosine, biotin-11-dUTP, biotin-16-dUTP and 7-deaza dGTP) and dUTP may also be used as substrates, e.g., to introduce deliberate point mutations.

Primers 0.2–1.0 µM Primers are pair of short pieces of DNA, typically 15–30 bases long that hybridize to complementary strands, flanking the region of interest on to target template (Fig. 5.4). The primer-target hybrid then allows DNA polymerase enzyme to initiate incorporation of the deoxynucleotides. In conventional PCR, two primers are used, one (➀) that anneals to the 3′end of the sequence on one strand and is extended inward with DNA polymerase from the 3′end of the primer. The second primer (➁) anneals to the 3′end of the second strand and is also extended inward from the 3′end (Fig. 5.4). Primers can either be specific to a particular DNA nucleotide sequence or can be “universal,” i.e., complementary to a very common nucleotide sequence present in the set of DNA molecules.

DNA polymerase 2.5 U/100 µL A thermostable DNA polymerase enzyme that synthesizes the new DNA molecule by adding deoxynucleotides to the 3′ end of annealed primer.

MgCl2 0.15 mM It is the major constituent responsible for fidelity of PCR reaction. Mg++ ions acts as coactivator of DNA polymerase and helps in primer annealing and incorporation of dNTPs. Concentration of MgCl2 is extremely critical since too little free magnesium ion will result in little or no PCR product, and too much free magnesium ion may produce a variety of unwanted products and promote misincorporation.

Template 0.05–1.0 µg It is the target sequence that needs to be amplified. It may be single- or double-stranded DNA or RNA. Generally, nanogram of cloned template or microgram of genomic DNA is required as the starting template for amplifying a target sequence, since DNA is more stable and can be isolated easily.If RNA is to be utilized as template, the first amplification cycle will lead to complementary DNA (cDNA) through an added step using reverse transcriptase.The length of template strand selected should cover the target sequence to be amplified. The target sequence to be amplified is generally highly specific and occurs only once (monomorphic) in the genomic DNA of the organism.


Figure 5.4. Steps in a typical PCR.


sequence very closely matches the template sequence and the process is called primer annealing. DNA polymerase then binds to the “primer-template” hybrid and begins DNA synthesis.

Step III. Primer extension: DNA Polymerase bound onto “primer-template” hybrid begins synthesis of a new DNA strand complementary to the DNA template by adding nucleotides to the 3′OH ends of annealed primers of both DNA strands at 72°C. Generally, thermophilic DNA polymerase catalyzes tem-plate-directed synthesis of DNA from nucleotide triphosphates in presence of magnesium ions. Generally, thermophilic DNA polymerases have maximal catalytic activity at 75–80°C, and are almost inactive at lower temperatures. Most well-known thermo-stable DNA polymerases are:1. Taq polymerase, isolated from the hot springs bacterium Ther-

mus aquaticus.2. Pfu polymerase, having 3′–5′ exonuclease activity and isolated

from Pyrococcus furiosus.3. Vent polymerase, having 3′–5′ exonuclease activity and isolated

from Thermococcus litoralisThis process of denaturation, annealing, and primer exten-

sion is repetitively followed to achieve a large amount of amplified DNA product of desired region. Since both strands are copied dur-ing PCR, there is an exponential increase of the number of copies of the gene as shown in Fig. 5.5. Every thermal cycle would double

Figure 5.5. Exponential amplification process in PCR.


the number of template DNA for next cycle, the number of DNA products can be calculated [Eq. (5.1)].

Step IV. Termination: This step is meant to terminate all the reactions going on in the PCR reaction mixture, generally achieved by bringing the temperature to 4°C after about 30–35 cycles of extension at 72°C. The time required to traverse from one temper-ature to another is referred to as the ramp time and usually con-tributes significantly to the total thermal cycling time.

PCR generated product can be analyzed using a variety of detec-tion methods like gel electrophoresis, spectroscopy, fluorescent labeling, and autoradiography. Among these, gel electrophoresis is the simplest and most popular method. Gel electrophoresis (using agarose or polyacrylamide) involves separation of biomolecules (such as deoxyribonucleic acid (DNA), ribonucleic acid (RNA), or protein molecules) using an electric field. Different-sized mole-cules form distinct bands on the gel depending on charge to mass ratio and from separate bands, which can be visualized after stain-ing with dyes like ethidium bromide, or silver, or Coomassie bril-liant blue.

The basic equation describing PCR amplification is

N N E( 1)c 0c= + (5.1)

where c is the number of thermocycles, E is the amplification efficiency (also expressed as % E = E × 100%), N

c is the number

of amplicon molecules, and N0 is the initial number of target

molecules.PCR amplification process is highly sensitive to various factors

like constituents of the reaction mixture and the reaction condi-tions. Following are the major factors that must be considered prior to setting up a PCR:1. Primer length, specificity, and G/C content: The primers are typi-

cally between 15 and 30 bases long. The composition of the two primer sequences must ensure specific annealing to the target sequence alone. The probability of this specificity can be made through a search in the computer databases (GenBank or EMBL). The primers should not contain bases complementary to them-selves or with each other otherwise the two primers will “self-anneal” to form primer-dimer products and will give possible false negative analysis. A + T (40%) to G + C (60%) content is rec-ommended for each primer, avoiding internal secondary struc-ture and long stretches of any one base. Also, primers should not sit on regions of secondary structure (within the target) having a higher melting point than the primer. Nontemplate, comple-mentary 5′ extensions may be added to primers to allow a variety of useful post amplification manipulations of the PCR product

Nc=N0(E+1)c


without significant effect on the amplification itself. These 5′ ex-tensions can be restriction sites, promoter sequences, etc.

2. Melting temperature (Tm

): Melting Temperature (Tm

) is the tem-perature at which the double-stranded (ds) DNA target will dissociate to become single stranded and will allow annealing of primer sequence. Primers with melting temperatures in the range of 52°C to 58°C generally produce the best results. Prim-ers with melting temperatures above 65°C have a tendency for secondary annealing. T

m is dependent on primer length and

sequence that are of critical importance in designing the pa-rameters of a successful amplification as the melting tempera-ture of nucleic acid duplex increases with its length, and GC content. A simple formula for calculation of the [T

m(Eq. 5.2)] is

T 4(G C) 2(A T) Cm = + + + ° (5.2)

where (G + C) = Total number of G and C in the primer (A + C) = Total number of A and T in the primer.

4. Primer annealing temperature (Ta): The melting temperature

(Tm

) is the estimate of the DNA-DNA hybrid stability and is critical in determining the annealing of primer with template. Too high T

a will produce insufficient primer-template hybrid-

ization resulting in low PCR product yield. Too low Ta may pos-

sibly lead to nonspecific products caused by a high number of base pair mismatches. Mismatch tolerance is found to have the strongest influence on PCR specificity and may result in false results. Primer annealing temperature (T

a) can be calculated

[Eq. (5.3)] as follows:

T T T0.3 (primer) 0.7 (product) 14.9a m m= × + × − (5.3)

where Tm

(primer)

= Melting Temperature of the primers, Tm

(prod-

uct) = Melting temperature of the product.

4. Values for Tm

: An important consideration in primer designing is to ensure that the 3′ and 5′ primers do not have very different values for T

m. Primers with T

m greater than 5°C difference may

result in the imbalanced amplification and decrease in yield or even no amplification.

5. Avoid repetition of single nucleotide base: Primer having more than three single nucleotide base repetition may result in primer breathing (self-annealing) and in mispriming. There-fore, primers with long runs of a single base should generally be avoided, for example, the sequence AGCGGGGGATGGGT has run of five for the base G.

6. False positive and false negative outcomes: PCR is based on DNA amplification where chances there are larger chances of false-positive or false-negative outcomes (Kwok & Higuchi, 1989).

Tm=4(G+C)+2(A+T)°C

Ta=0.3×Tm (primer)+0.7×Tm (product)−14.9


Primary cause of false positive has been identified as carryover of amplified product from previous reaction pipetting devices, laboratory surfaces, or even the skin of workers (Kitchin, Szoty-ori, Fromholc, & Almond, 1990). This can be controlled through careful pipetting and creating physical barrier between source reagents and positive/negative controls.PCR due to ease of amplification process and flexibility of

manipulating the reaction parameters has gained larger impor-tance among the researchers. PCR-based bacterial detection in various matrices including food, water, and clinical specimens (such as blood, urine, sputum, and cerebrospinal fluid-CSF) gen-erally may vary due to its constituents and amount available, and it essentially requires careful customized design of PCR assay for each specific specimen (Yamamoto, 2002). PCR and its recently grown variants are offering very important protocol for diagnosis of microbe, which are even very difficult to culture. It has opened the doors to further developments in the basic process due to ver-satility and possibility to introduce certain modifications to the standard PCR protocol. Some of the generally used modifications for the detection of foodborne pathogens are described in next sections.

3.2 Nested PCRNested PCR or nPCR results in higher specificity in identifying

the food pathogen. In conventional PCR, the designed primers are generally complementary to the termini of the target DNA. If the same sequence is repeated in other parts of template, primers may bind to these incorrect regions of the DNA and may result in amplification of unwanted products. nPCR is a modification of basic PCR developed to increase the specificity of amplified PCR products by decreasing unexpected primer amplification that otherwise may be leading to contamination in products.

Nested PCR (Fig. 5.6) involves two sets of primers, which are used in two successive runs of polymerase chain reaction. In the first amplification reaction, first set of primer (outer in red color) is used to generate DNA products, which, besides the intended tar-get, may still consist of nonspecifically amplified DNA fragments. The product(s) are then used in a second PCR with a second set of primers (inner in green color) whose binding sites are com-pletely or partially different from first set and is located at 3′ end of the first set of primers used in the first reaction. Nested PCR allows a greater level of amplification as target sequence is ini-tially amplified by an external pair of primers for 20–40 cycles, and PCR product generated in first PCR reaction serves as template for


second amplification process or reaction for 20–40 cycles using the second set of primers. The secondary amplification would not occur if the primary amplification was nonspecific. Many food-borne pathogens have been detected and characterized using this method (Kim, Kim, Kwon, Lee, & Oh, 2008; Klemsdal & Elen, 2006; Saroj, Shashidhar, Karani, & Bandekar, 2008). A major limitation of this technique is that the reaction vessel needs to be opened in order to add the second primer set in the reaction mixture and this increases the chances of contamination.

3.3 Multiplex PCRMultiplex PCR (mPCR) was first described by Chamberlain et al.

(1988), which enables simultaneous amplification of many targets of interest in one reaction by using more than one pair of prim-ers. This method has been applied in many areas of DNA testing

Figure 5.6. Nested PCR with two sets of primers outer (in red color) and inner (in green color).


(such as deletions, mutations, and polymorphisms, or quantita-tive assays), genotyping applications where simultaneous analysis of multiple markers is required, detection of pathogens or geneti-cally modified organisms (GMOs), or microsatellite analyses. Multiplex PCR can lead to formation of two or more amplicons from separate regions of target DNA. mPCR may be used as the endpoint of analysis, or preliminary to analysis like sequencing or hybridization. Multiplex PCR has shown advantages for low-cost, multiple detection of pathogen and requirement of low volume of test sample in a single PCR experiment. A key factor in the devel-opment of multiplex PCR assay is the design of the primers, as all of the primers must be designed with very close annealing tem-perature. The amplification products also need to be at markedly different sizes so as to be easily and distinctly visualized through agarose gel electrophoresis. Closely related templates such as pathogen strains can be distinguished by amplifying different sequence, using primers for a sequence common to all templates (Bej et al., 1990; Bej, McCarty, & Atlas, 1991; Kaltenboek, Kansoulas, & Storz, 1992; Way et al., 1993; Wilton & Cousins, 1992). For some cases, designing of multiplex PCR systems may be as simple as combining two sets of primers for which reaction conditions have been determined separately. Care must be taken while selecting the regions to be amplified and relative sizes of the amplified frag-ments, primer dynamics, and PCR parameters such that multiple fragments can be accommodated. Multiplex amplicons that dis-tinguish similar templates, such as virus types, bacteria strains, or gene alleles, are ideally located in regions that are not extremely variable, where any given amplicon might contain the sequence of several genotypes (Repp et al., 1993).

Primers have to be designed that their predicted hybridiza-tion kinetics are similar to those of other primers in the multi-plex reaction. A G/C content of 40%–60% and average length of 23–28 nucleotides are suggested as general guidelines for specific annealing at moderate temperatures (Gibbs, Chamberlain, & Caskey, 1989). Conditions for each set of primers should be devel-oped individually and modified if necessary as primer sets are added. The possibility of nonspecific priming and other artifacts can increase with each additional primer. Thus, primer pairs those give a “clean” signal alone but produce artifact bands in multiplex may be corrected using “hot-start” PCR (Zazzi, Romano, Brasini, & Valensin, 1993), addition of organics, annealing at the highest possible temperature. If all else fails, reselection of the primer sequence can be done when all primer pairs are not at all com-patible, and subgrouping them in smaller multiplexes would serve the purpose.


To achieve a robust mPCR, it may be necessary to adjust con-centrations of various reaction components using appropriate buffering system. Mg2+ and nucleotide requirements generally increase with the number of amplicons in the multiplex, but other concentrations must be optimized because each primer pair may have different requirements (Chamberlain, Gibbs, Ranier, & Caskey, 1992). Likewise, polymerase requirements generally increase with the size of the multiplex. Similarly, thermocycling parameters have to be standardized as extension time should be increased as per the number and highest length of target to be amplified in the reaction.

Multiplex systems developed for microorganism detection are able to distinguish pathogens or even species/strains of the same genus. An amplicon of sequence conserved among several groups can be included in the reaction to indicate the presence of phylogenetically or epidemiologically similar, or environmentally associated, bacteria. Multiplex assays have been utilized to distinguish species of Legionella (Bej et al., 1990), Mycobacterium (Wilton & Cousins, 1992), Salmonella (Way et al., 1993), Escherichia coli, and Shigella (Bej et al., 1991) and major groups of Chlamydia (Kaltenboek et al., 1992) from other genus members or associated bacteria. Multiplex assays can also differentiate the forms of the toxin-producing pathogens like E. coli (Gannon, King, Kim, & Gotsteyn Thomas, 1992) and yeast (Pearson & McKee, 1992). Although, multiplex PCR technique is very powerful for running repeated multiple assays. It is difficult to set up the primers for an assay for the first time. It may take extensive trials to find primers and probes, which do not have any problems like cross-hybridization or mishybridization of unintended locations. The whole reaction process is tedious and time-consuming to establish that require lengthy optimization procedures.

3.4 Reverse transcription (rt) PCRReverse transcription or rt-PCR is a technique in which RNA is

used as a template to produce amplified product. RNA is present in all actively growing and replicating cells; unlike DNA, RNA tends to degrade rapidly in dead cells. rt-PCR assays require intact and measurable quantities of RNA to generate pathogen-specific sig-nal, screening animals and foods of animal origin for determining the presence of live bacterial cells (Sharma, 2006). Therefore, rapid detection of bacterial pathogens can prompt a quicker remedial action for removing carrier animals or contaminated foods from the food chain.


rt-PCR is a two-step technique that involves the Reverse Transcription reaction and PCR amplification as shown in Fig. 5.7 F. Reverse transcription is a process in which single-stranded RNA is reverse transcribed into complementary DNA (cDNA) by using total cellular RNA or poly (A) RNA, a reverse transcriptase enzyme (RNA dependent DNA polymerase), a primer, dNTPs and a RNase inhibitor. RNase H leaving cDNA in the reaction mixture degrades the original RNA template. Then resulting cDNA is used as tem-plate for subsequent PCR amplification using primers specific for one or more genes. Reverse transcription is also called first-strand cDNA synthesis. Reverse transcription is a very important step to perform PCR since DNA polymerase can act only on DNA tem-plates (Hunt, 2006). A second strand of DNA is synthesized through the use of a deoxyoligonucleotide primer and a DNA-dependent DNA polymerase as in a PCR. Three types of primers can be used for RT reaction: oligo (dT) primers, random (hexamer) primers, and gene-specific primers. The cDNA and its antisense counter-part are then exponentially amplified.

Figure 5.7. Synthesis of cDNA from mRNA using reverse transcriptase enzyme followed by PCR amplification.


rt-PCR can give better sensitivity to detect genes of food-borne viral pathogens via RNA (Arnal, Ferre-Aubineau, Mignotte, Imbert-Marcille, & Billaudel, 1999; Gilgen et al., 1995; Hewitt & Greening, 2006; Wang et al., 2008). The expression of certain genes during the course of growth or infection is in much higher number of messenger or ribosomal RNA compared to the number of DNA copies present. However, RNA is unstable, and reverse transcrip-tion PCR is therefore more skillful at handling when quantification is required for detection of foodborne pathogen. Since excessive RNA is present in every growing and replicating cell, unlike DNA, they tend to degrade in dead cells. Therefore, this technique can-not be utilized to detect dead cells or its toxins.

The conventional rt-PCR is a time-consuming technique with some important limitations such as use of ethidium bromide that gives low sensitivity and yields results that are not always reliable. Moreover, there is an increased cross contamination risk of the samples since detection of the PCR product requires the postam-plification processing of the samples. However, the most impor-tant issue concerning conventional rt-PCR is the fact that it is a semi- or even a low-quantitative technique, where the amplicon can be visualized only after the amplification ends. Therefore, the technique was further modified to real time PCR, a method in which the amplicons are visualized with amplification progress using a fluorescent reporter molecule.

Some recent examples of PCR-based detection reveal that minimum of 12 h pre-enrichment (buffered peptone water) is required for detection of Salmonella by PCR at a limit of 100 col-ony forming unit (cfu)/1 ml of sample (i.e., Chicken meat samples (ground, boneless/skinless breast meat, and bone-in breast meat with skin) from retail grocery stores) (Myint, Johnson, Tablante, & Heckert, 2006). This method utilized Salmonella-specific primers ST 11 and ST 15 to amplify a 429 bp region of random fragment target specific to all Salmonella spp.

3.5 Real-time (RT) PCRReal-time PCR or RT PCR or q PCR (quantitative PCR) is sec-

ond generation of PCR developed by Higuchi and collaborators in 1992. It was designed to do PCR amplification and real-time product verification/visualization in one single run by using a target-specific fluorescent probe in reaction master mix, elimi-nating post-PCR analysis process (Higuchi, Fockler, Dollinger, & Watson, 1993). This results in shortening of detection time and reducing the risk of amplicon contamination by laboratory envi-ronments (Klein & Kuneja, 1997).


Detection of PCR products is dependent on the generation of a fluorescent signal during or post probe annealing with its com-plementary DNA target or association of dye with the product. The signal is readily monitored on a computer screen where each point is automatically plotted and the extent of amplification is followed as continual direct graphical plot. Computer software handles all of the preprogrammed calculations and data plotting. RT-PCR systems rely upon detection and quantitation of a signal generated from a fluorescent reporter that increases in the direct proportion to the amount of PCR product or amplicon generated.

Detection of RT-PCR products is monitored using different strategies. One of them is via monitoring ultraviolet (UV)-induced fluorescent signal proportional to the quantity of synthesized DNA. Presently, four different fluorescent labels/probes (viz. TaqMan probes, Molecular Beacons, Scorpions and SYBR Green) are avail-able for real-time PCR (Aliyu et al., 2004; Churruca et al., 2007; Houde et al., 2007; Lambertz, Nilsson, & Hallanvuo, 2008; Nam, Srinivasan, Murinda, & Oliver, 2005; Rensen, Smith, Jaravata, Osburn, & Cullor, 2006; Sandhya, Chen, & Mulchandani, 2008; Zhou, Hou, Li, & Qin, 2007, Casas, Amarita, & de Maranon, 2007). TaqMan probes, Molecular Beacons, and Scorpions depend on Forester Resonance Energy Transfer (FRET) to generate the fluo-rescence signal having a fluorogenic dye molecule and a quencher moiety attached to the same or different oligonucleotide sub-strates. SYBR Green is a fluorogenic dye that exhibits little fluores-cence when in solution, but emits a strong fluorescent signal upon binding to double stranded DNA.1. TaqMan probes: TaqMan probes (Fig. 5.8A) are oligonucle-

otides that have a fluorescent reporter dye attached to the 5′ end and a quencher moiety coupled to the 3′ end. These probes are designed to hybridize at internal region of a PCR product (Fig. 5.8B). TaqMan probes depend on the 5′-nuclease activ-ity of the DNA polymerase during PCR such that reporter oli-gonucleotide (TaqMan) hybridized to the target amplicon is hydrolyzed during amplification process to yield fluorescent signal (Fig. 5.8C). In the nonhybridized state, the proximity of the fluorophore and the quencher molecules prevents the de-tection of fluorescent signal from the probe and the phenom-enon is called FRET. Hybridization decouples the fluorophore and quencher leading to emition of fluorescence that continue to increase in each cycle, proportional to the amount of probe cleavage (Fig. 5.8D). TaqMan probes can be used for multiplex assays by designing each probe with a spectrally unique fluo-rophore/quench pair and also for quantification of the target foodborne pathogen.


2. Molecular beacons: Molecular beacons (MBs) are oligonucle-otide probes that can report the presence of specific nucleic ac-ids in homogenous solutions (Tyagi & Kramer, 1996). They use phenomena of FRET to detect and quantitate the synthesized PCR product in real-time monitoring systems. MBs (Fig. 5.9) are hairpin or stem-loop structures specially designed in a way that the loop portion of the probe contains sequence comple-mentary to a target nucleic acid molecule. The stem-loop or hairpin structure is formed by the annealing of complemen-tary arm sequences having a fluorescent moiety attached to the end and a quenching moiety to the other end. The stem keeps these two moieties in close proximity to each other, causing the fluorescence of the fluorophore to be quenched by energy transfer, that is FRET. Since the quencher moiety is a nonfluorescent chromophore and absorbs the energy received from the fluorophore and remits as heat. The probe is therefore unable to fluoresce during the phenomenon called collisional (or proximal) quenching (Fig. 5.9A). In the presence of a com-plementary sequence, the probe unfolds and hybridizes to the

Figure 5.8. RT-PCR using TaqMan probes. (A) TaqMan probe containing a reporter dye (•) at the 5′end and a quencher (•) at the 3′ end. (B) Annealing of TaqMan probe to target amplicon. (C) PCR amplification to produce a complementary DNA strand and 5′ exonuclease activity of Taq polymerase to remove reporter dye, and (D) Fluorescence emission of reporter dye after its separation from quencher.


target displacing the fluorophore from the quencher so that no longer the photons emitted by the fluorophore are absorbed by the quencher. Thus, the amount of signal generated as fluores-cence is proportional to the amount of target sequence, and is measured in real-time to allow quantification of the amount of target sequence (Fig. 5.9B). To detect multiple targets in the same solution, molecular beacons can be made utilized with different or broad range of fluorophores (Tyagi, Bratu, & Kram-er, 1998) during multiplex assays via spectrally separated fluo-rophore/quench moieties on each probe.

3. Scorpions: Scorpion probe-based technique was described by Dr. David Whitcombe of DxS Ltd. for sequence-specific prim-ing (Whitcombe, 2011). These are bifunctional molecules con-sisting of a detection probe (stem-loop structure) covalently linked to a quencher (•) at 3′ end and a fluorophore (•) at the 5′ end of primer as shown in Fig. 5.10A. The Scorpion probe contains a self-complementary stem sequence that maintains a stem-loop configuration in the unhybridized state that holds the amplicon-specific region in this hairpin loop. The fluoro-phore and quencher are held in close physical proximity by the stem structure, thereby ensuring efficient suppression of fluorescence prior to thermocycling (FRET). It contains a PCR blocker (in green color Fig. 5.10) at the start of the hairpin loop

Figure 5.9. RT PCR using MBs: (A) target sequence and hairpin or stem-loop MB exhibiting FRET and (B) Hybridized MB to target DNA resulting in fluorescence emission.


at 3′ end, which prevent read-through by the polymerase to generate complementary DNA of stem-loop region. In the ini-tial PCR cycles, the primer hybridizes to the target and gener-ates the complementary sequence using polymerase enzyme (Fig. 5.10B). DNA duplex formed after first PCR cycle when denatures (Fig. 5.10C), amplicon-specific region of hairpin loop hybridizes to the complementary sequence present on newly synthesized strand, thus opening up the hairpin loop (Fig. 5.10D). During the Scorpion PCR reaction, the fluorophore and the quencher separate with the bending and hybridization of loop sequence to target sequence, leading to an increase in the emitted fluorescence (Fig. 5.10E). The fluorescence can be detected and measured in the reaction tube. Denaturation of the hairpin loop requires less energy than the new DNA du-plex produced. Scorpion primers can be used to examine and identify point mutations by using multiple probes where each probe is tagged with a different fluorophore to produce differ-ent colors.

4. SYBR green: SYBR Green is among the most sensitive, sim-plest, and economical choice available for detection of double stranded DNA that upon excitation emits fluorescent light directly proportional to the PCR product amplified in real-time PCR (Fig. 5.11). For single PCR product reactions with well-designed primers, SYBR Green can work extremely well, distinguishing spurious nonspecific background by showing fluorescence in very late cycles. Since the dye binds to dou-ble-stranded DNA, there is no need to design a probe for any particular target being analyzed. However, detection by SYBR

Figure 5.10. Scorpion probes for RT-PCR.


Green requires extensive optimization. The dye cannot distin-guish between specific and nonspecific product like primer di-mers accumulated during PCR. Generally, over estimation of the actual data occurs; therefore, follow-up assays are needed to validate results.

In the present-day situation, PCR and quantitative polymerase chain reaction (qPCR) are essential analytical tools for foodborne pathogens detection. Development of Multiplex qPCR allows the simultaneous detection of more than one pathogen in one single reaction, saving considerable effort, time, and money. This ampli-fication process in real time is really fast, easy to perform, have extremely wide dynamic range of quantification (more than eight orders of magnitude), and provide significantly higher reliability and sensitivity of the results. Since the first scientific work was published in 1996 (Heid, Stevens, Livak, & Williams, 1996), the number of qPCR-based publications has increased nearly expo-nentially. Specific detection and quantification of major pathogens found in food by qPCR have been evaluated for a wide variety of microorganisms such as Salmonella spp., L. monocytogenes, E. coli

Figure 5.11. SYBR green binding to minor groove of double-stranded DNA for RT-PCR.


O157:H7, and Staphylococcus aureus, among others (Rodríguez-Lázaro & Hernández, 2013) where detection time can be decreased down to 24 hours for most of these bacteria.

3.6 Digital PCR (dPCR)Digital PCR (dPCR) is a novel method devised for precise quan-

tification of nucleic acids. First publication reporting “Minimum Information for Publication of Quantitative dPCR Experiments” was published by Huggett et al. (2013). Michael Samuels from Rain Dance Technologies, USA has described that dPCR provides absolute quantification without the need for standard curves and uses similar assay reagents as used in standard analog measure-ments, but counts the total number of individual target molecules in a digital format, enabling many applications that require high sensitivity and have restricted sample availability (Samuels, 2017).

Basically, digital PCR measurements utilize measurement of fluorescent signals generated through endpoint PCR amplifica-tion of the sample or qPCR mixture, which is predivided into very large number of separate small volume reactions (such that there is either zero or one target molecule present in any individual reaction, generally 10000, 1,00,000 partitions) (Bustin et al., 2005; Rutledge & Cote, 2003; Tsiatis et al., 2010; Prediger, 2013) (Fig. 5.12).

Positive and negative PCR signals are indicated by “bright or dark” fluorescence and noted as digital signal (1 and 0, respec-tively) measurement describing presence or absence of tar-get in the compartments. Here, the number of positive reaction

Figure 5.12. Digital PCR or dPCR uses division of the sample and the assay (e.g., qPCR hydrolysis probe and primers) into various separate reaction chambers so as to achieve either only 0 or 1 target molecule per chamber. Subsequent to standard endpoint PCR number of fluorescent reactions counted for “bright” and “dark” reactions indicating PCR positive containing one positive target molecule and PCR negative containing no target (as adapted from Prediger, 2013;© 2020 Integrated DNA Technologies).


compartments will indicate the total number of targets present in the entire sample volume (the total number of reactions mul-tiplied by the individual reaction volume equals the total volume assayed). Therefore, absolute concentration of target can be esti-mated as Eq. (5.4):

Absolute concentration of targettotal number of target molecules

total measured volume=

(5.4)

The only possible errors in this measurement arise when more than one target molecule is present in the compartment or when there is error in the volume measurement. In significantly smaller number of targets, chances of co-localization of target molecules are very less. If needed, colocated target molecules in same com-partment can be calculated using Poisson statistics (Dube, Qin, & Ramakrishnan, 2008; Whale et al., 2012). Higher the number of compartments, highest will be the sensitivity with detection limit approaching 1 in a million. dPCR is not likely to replace all qPCR assays in the clinical laboratory. The lower throughput and lon-ger turnaround times of current dPCR systems compared to qPCR argue against their routine implementation. Digital PCR as qPCR is based on the polymerase chain reaction principle and utilizes fluorescently labeled probes or DNA intercalating dye. dPCR works by partitioning PCR mix into many individual small-volume PCR reactions that may vary from 20,000 partitions whereas in droplet digital PCR (ddPCR), up to 10 million droplets can be generated with the help of special kind of oil.

Digital PCR (dPCR) allows the precise quantification of nucleic acids, facilitating the measurement of small percentage differ-ences and quantification of rare variants. It was reported to be more reproducible and less susceptible to inhibition than qPCR. Its main applications are rare variant measurement, molecular counting, and applications with higher precision. This method has not been used till now for detection of microbes but of course when its features are examined, it can be extrapolated that this method has potential to use more than one microbe and even differentiate very small variations in the closely related species. Droplet digital PCR (ddPCR) is commercial version of available dPCR approaches that makes use of special oil base, which facili-tates formation of very small droplets of the sample. This tech-nology is reported to quantify low amounts of Bacillus cereus in milk (Porcellato, Narvhus, & Skeie, 2016), and Bifidobacterium and Lactobacillus in breast milk of healthy women (Qian, Song, & Cai, 2016).

Absolute concentra-tion of target=total num-

ber of target moleculesto-tal measured volume


4 Advanced molecular techniques for detection of foodborne pathogens

With the increasing concern about food quality control-related issues, alternative and advanced versions of molecular techniques have been developed that help overcome the shortcomings of existing PCR methods like use of thermal cycler, complicated reaction optimization process, and use of labels. Following are some other techniques that address some of these concerns about the existing PCR-based molecular detection protocols.

4.1 Loop-mediated isothermal amplificationIsothermal DNA amplification techniques, such as loop-medi-

ated isothermal amplification (LAMP), are suitable, rapid, and onsite detection techniques for food pathogens because of its ability to amplify DNA with high specificity, efficiency, and speed without thermal cycling. LAMP (Notomi et al., 2000) is an out-standing gene amplification procedure, in which the reaction can be processed at a constant temperature by one type of enzyme, where it is rapid and simple features make it clearly different from the existing genetic tests. Unlike PCR, a denatured template is not required (Nagamine, Watanabe, Ohtsuka, Hase, & Notomi, 2001) to generate large amount of DNA. In a short span of time, posi-tive LAMP reactions can be visualized with the naked eye (Iwasaki et al., 2003; Mori, Nagamine, Tomita, & Notomi, 2001). As men-tioned earlier, the main advantage of this technique is its simplic-ity where only a water bath or heating block is needed to provide a constant temperature as the amplification proceeds under iso-thermal conditions.

The LAMP method employs a special DNA polymerase (Bst DNA polymerase) and a set of four specially constructed prim-ers (F2, F3, B2, and B3) that recognize six distinct regions on the target DNA as shown in Fig. 5.13. An inner primer (F2 or B2) with sequences of sense and antisense strands of the target ini-tiates LAMP. A pair of “outer” primers (F3 or B3) then displaces the amplified strand with the help of Bst DNA polymerase, which has a high displacement activity, to release a single-stranded DNA, which then forms a hairpin to initiate the starting loop for cyclic amplification as shown in Fig. 5.13. Amplification proceeds in cyclic order, each strand being displaced during elongation with the addition of new loops with every cycle. The final products are stem-loop DNAs with several inverted repeats of the target and cauliflower-like structures having multiple loops due to hybrid-ization between alternately inverted repeats in the same strand


Figure 5.13. Loop-mediated isothermal amplification (As adapted from Notomi et al., 2000).


(Notomi et al., 2000). The reaction can be accelerated by using two extra loop primers (Nagamine, Kuzuhara, & Notomi, 2002).

4.1.1 Primers for LAMPA set of two inner (F2 or FIP, B2 or BIP) and two outer (B3 and

F3) primers are required for LAMP at both forward and back-ward locations (Fig. 5.12). All four primers are used in the initial steps of the reaction, but in the later cycling steps, only the inner primers are used for strand displacement synthesis. The special feature about FIP (Forward inner primer) and BIP (Backward inner primer) is that it contains an added complementary primer sequence (cF1 and cB1, respectively) at 5′ end of the inner primers (F2 and B2) that will self-hybridize later on with the newly synthe-sized strand to give a loop-like structure (Notomi et al., 2000). The size and sequence of the primers were chosen so that their melt-ing temperature (T

m) is between 60 and 65°C, which is the optimal

temperature for Bst polymerase. The F1c and B1c Tm

values should be a little higher than those of F2 and B2 to form the looped-out structure. The T

m values of the outer primers F3 and B3 have to

be lower than those of F2 and B2 to assure that the inner prim-ers start synthesis earlier than the outer primers. Additionally, the concentrations of the inner primers are higher than the concen-trations of the outer primers (Notomi et al., 2000). Furthermore, it is critical for LAMP to form a loop-like structure on amplicon DNA to from a dumb-bell structure. Various sizes of loop between F2c and F1c and between B2c and B1c were examined and best results are given when loops of 40 nucleotides (40 nt) or longer are used (Notomi et al., 2000). The size of target DNA is an important factor that LAMP efficiency depends on because the rate-limiting step for amplification is strand displacement DNA synthesis. Various target sizes were tested and the best results were obtained with 130–200 bp DNAs.

4.1.2 Steps of LAMP processLAMP relies on auto-cycling strand displacement DNA synthe-

sis, which is carried out at 60–65°C for 45–60 min in the presence of Bst DNA polymerase, dNTPs, specific primers, and the target DNA template. The mechanism of the LAMP amplification reac-tion as illustrated in Fig. 5.13 includes three steps: production of starting material, cycling amplification, and elongation and recy-cling (Notomi et al., 2000).

Production of starting material: To produce the starting mate-rial, inner primer FIP hybridizes to F2c in the target DNA (step 1) and initiates complementary strand synthesis (step 2). Outer


primer F3 hybridizes to F3c in the target (step 3) and initiates strand displacement DNA synthesis (step 4), releasing a FIP-linked complementary strand (step 5), which forms a looped-out struc-ture at one end (step 6). This single-stranded DNA serves as tem-plate for BIP-initiated DNA synthesis (step 6) and subsequently B3 initiating primed strand displacement DNA synthesis (step 7) leading to the production of a dumb-bell form DNA, which is quickly converted to a stem-loop DNA (step 8). This then serves as the starting material for LAMP cycling, the second stage of the LAMP reaction.

Cyclic amplification: FIP hybridizes to the loop in the stem-loop DNA to F2c (step 9) and primes strand displacement after complementary strand is synthesize through F1 loop (step 8), leading to a loop formed at the opposite end via the BIP sequence (step 9). This is followed by self-primed strand displacement DNA synthesis through B1 loop yielding one complementary structure of the original stem-loop DNA (step 11) and hairpin stem-loop DNA (step 10). These products (steps 10 and 11) then serve as templates for BIP-primed strand displacement in the subsequent cycles generating the amplified products (steps 12 and 14). Step 14 through F1 self-priming generates dumb bell form DNA (as step 8) and hairpin stem-loop DNA (step 15).

Elongation & recycling: Steps 10 and 15 are followed by the sub-sequent elongation and recycling and the final product is a mixture of stem-loop DNA with various stem length and cauliflower-like structures with multiple loops. Loop formation occurs due to annealing of alternately inverted repeats of the target sequence in the same strand (Notomi et al., 2000).

4.1.3 Visualization of LAMP amplification productsAfter certain cycle of the positive LAMP reactions the turbidity

in the reaction mixture increases, which can be monitored in real time with a turbidimeter. The turbidity is derived from precipita-tion of magnesium pyrophosphate generated as a by-product and this correlates with the amount of DNA amplified.

Positive LAMP reactions can be detected using agarose gel elec-trophoresis, followed by gel staining with an intercalating agent such as ethidium bromide (EtBr) to visualize ladder-like structure from the minimum length of target DNA up to the loading well under UV light. This characteristic banding pattern is observed due to various length stem-loop products of the LAMP reaction. Alternatively, SYBR Green is among most sensitive, simplest, and economical choice available for detecting double-stranded DNA. SYBR green upon excitation emits fluorescent light directly pro-portional to the product amplified in LAMP (Karleson, Steen, &


Nesland, 1995). Addition of a fluorescent detection reagent (FDR) to the LAMP reaction mixture before starting the amplification allows the product to be directly visualized under UV illumina-tion and decreasing the chances of contamination, for example, Calcein in the FDR combines initially with magnesium ions and remains quenched. As the LAMP reaction progresses, pyrophos-phate ions are produced as a by-product that binds and removes magnesium from the calcein resulting in detectable green fluo-rescence, indicating the presence of amplified target genes (Imai et al., 2007; Yoda et al., 2007). A photo redox system, that is, a low-molecular-weight poly (iminoethylene) dye (PEI) can be added to the LAMP product after centrifugation for 10 s at 6000 rpm. It forms an insoluble dye-product (amplified DNA) complex that can be visualized for its fluorescence under conventional UV illu-minator or by fluorescence microscopy (Mori et al., 2006).

4.2 Nucleic acid sequence-based amplificationNucleic acid sequence-based amplification (NASBA) was

developed by Jean Compton in 1991 at Mississauga, Canada, and the technique was first described by Kievits (1991). NASBA relies on the isothermal amplification of RNA and has been reported as useful tool for the quick detection of microbial pathogens in food and environmental samples (Cook, 2003). Compared to PCR method, NASBA was developed as an alternative to RNA amplifi-cation, which specifically amplifies RNA without thermal cycling, but not DNA (Heim, Grumbach, Zeuke, & Top, 1998). NASBA is based on the simultaneous activity of three enzymes: AMV reverse transcriptase, T7 RNA polymerase, and RNase H, without the intermediate addition of enzymes. T7 RNA Polymerase catalyzes the synthesis of RNA in the 5′→ 3′ direction in the presence of a DNA template containing a T7-phage promoter. NASBA amplifica-tion takes place using an RNA-dependent T7-polymerase using its specific promoter sequence tagged at 5′ end of primer 1 to gener-ate multiple RNA products at 41°C while maintaining the intact double-stranded DNA (Chan & Fox, 1999) as shown in Fig. 5.14. Standard reaction mixture for NASBA contains three enzymes (as mentioned above), nucleoside triphosphates, deoxynucleoside tri-phosphates, two specific primers (1 & 2), and require buffer com-ponents. Primer 1 consisting of a promoter sequence at 5′ to be recognized by T7 RNA polymerase and 3′ end complementary to 3′ side of target RNA and Primer 2 is complementary to the 5′ end of the synthesized cDNA strand. NASBA can be divided into three steps (Fig. 5.14) followed in “cycle” as new and increased number of RNA molecules will be available for next amplification cycle.


Step 1: cDNA synthesis: This step is considered as “noncyclic” phase of NASBA where primer 1 binds to the target RNA sequence allowing AMV reverse transcriptase to extend 3′ end by adding deoxynucleoside triphosphates to form a cDNA copy of target RNA sequence resulting in “RNA- cDNA hybrid.”

Step 2: Hydrolysis of RNA: Template RNA is hydrolyzed by RNase H; it only destroys RNA in RNA-DNA hybrids, but not sin-gle-stranded RNA.

Step 3: Amplification: Primer 2 anneals with the 5′end of the cDNA strand allowing the reverse transcriptase to form a double stranded cDNA copy of the original sequence. This double-stranded cDNA is then transcribed by T7 RNA polymerase by recognizing its promoter sequence and produces a complementary RNA strand

Figure 5.14. NASBA amplification for foodborne pathogen detection.


which can be used again in step 1, and thus the reaction will be in cyclic manner.

Subsequently, RNA molecules generated as product of NASBA reaction can be detected by gel electrophoresis followed by ethid-ium bromide staining.

Compared to RT-PCR for RNA detection, the major advantage of NASBA is elimination of DNase treatment step, in which NASBA amplification takes place at 41°C; at this temperature, the genomic DNA remains double stranded and does not become substrate for amplification, thereby eliminating the step for DNase treat-ment (Klein & Kuneja, 1997; Szabo & Mackey, 1999). The incuba-tion time for RNA amplification through NASBA is 90–150 min, whereas it is 3–5 h for RT-PCR to generate the same number of copies because in NASBA, every cycle results in an exponential increase, whereas PCR progresses in a binary fashion (Chan & Fox, 1999). NASBA has been utilized for several foodborne patho-gens such as Campylobacter spp., Cryptosporidium parvum, E. coli, Hepatitis A virus, Listeria monocytogenes, Rotavirus, and Salmonella. (Cook, 2003).

NASBA is a new phase of real-time monitoring for quantifica-tion of RNA viral particles (De Baar et al., 2001; Hibbitts, Rahman, John, Westmoreland, & Fox, 2003; Moore et al., 2004) and amplified RNA products can also be detected in real time using molecular beacons (Section 3.5, Leone, van Schijndel, van Gemen, Kramer, & Schoen, 1998; Tyagi & Kramer, 1996) for wide range of targets, for example, viruses, bacteria, parasites, and yeasts (Edwards, Logan, & Saunders, 2004).

4.3 OVATION amplificationA new methodology developed by Nugen (Nugen’s Ovation

RNA Amplification and Labeling Systems) involves a series of enzymatic reactions resulting in linear amplification of small amounts of RNA for array analysis (Fig. 5.15). Unlike exponential RNA amplification methods (e.g., NASBA and RT-PCR), Ovation amplification maintains representation of the starting mRNA population within 4 h. This process covers three steps - step 1 (similar to NASBA) and steps 2 & 3 are described below:

Step 2. Hydrolysis of RNA and Double-stranded DNA synthesis: Template RNA is digested by RNase H and poly DNA polymerase is used to synthesize the second strand of cDNA to get double-stranded DNA.

Step 3. Amplification: RNase H digests the primer 1 so that primer 2 (having T7 RNA polymerase promoter) can anneal. The


double-stranded cDNA is then reverse transcribed by the action of T7 RNA polymerase to generate mRNA; RNase H will degrade the previously annealed primer 2. Another primer 2 will anneal to the cDNA and T7 RNA polymerase will synthesize new mRNA generating thousands of RNA transcripts through transcription-ally active promoter.

Figure 5.15. OVATION amplification technology.


4.4 Multilocus sequence typingMultilocus sequence typing (MLST) has emerged as a new

powerful tool for the DNA typing of multiple loci for the evalu-ation of intraspecies genetic relatedness. This method relies on DNA sequence analysis of nucleotide polymorphisms in house-keeping genes and has shown a high degree of intraspecies dis-criminatory power for bacterial and fungal pathogens because the nucleotide sequence variation rate is relatively slow. MLST makes use of rapid sequencing technology to uncover allelic variants in conserved genes for the purpose of characterizing, subtyping, and classifying members of bacterial populations. It starts by using PCR to amplify sequences of several housekeeping genes subject to sequence analysis, and then to compare with each individual gene for differences. This method is finding a place in clinical microbiology and public health by providing data for epidemio-logical surveillance and development of vaccine policy.

MLST data analysis begins with the production of nucleotide sequences from targeted DNA regions. There are five steps to be followed for data typing, that is (1) Allele assignment, (2) sequence typing (ST) assignment, (3) data summary, (4) lineage assignment, and (5) estimation of recombinants. For MLST studies, approxi-mately 450–500 bp internal fragments of each gene are required. For each housekeeping gene, the different sequences present within a bacterial species are assigned different allele numbers and, for each isolate, the alleles at each of the loci define the allelic profile or subsequent sequence type (ST). The numbering sys-tem for this is arbitrary; consequently, each isolate is unequivo-cally characterized by a series of integers. A number of programs are available to compare the generated nucleotide sequence with nucleotide sequences from a database. One such program is the Sequence Typing Analysis and Retrieval System (STARS), which is an alternative interface to Staden package (fully developed set of DNA sequence assembly, editing, and analysis tools) for sequence assembly for sequence typing projects. With this software and good nucleotide sequence data, traces obtained from a 96-well microtiter plate can be assembled and alleles assigned in a mat-ter of minutes. Other software available is DiscoverIR (Licor, UK), which allows the assignment of an allele to each sequence vari-ant. However, if none of this software is available, then Web-based tools are available. For example, the Basic Local Alignment Search Tool (BLAST) is a set of search programs designed to explore all of the available sequence databases, regardless of whether the query is protein or DNA and these services are freely available on the Web by the National Center for Biotechnology Information (NCBI) in the USA. After allele assignment, data can be entered into the


appropriate section within the MLST website (http://www.mlst.net) to gain an ST. The STs are grouped into clonal complexes by their similarity to a central allelic profile, or genotype. These central genotypes are identified by a number of computer-based statistical methods. The clonal complex was first introduced for bacteria to describe populations of N. meningitidis (Maiden et al., 1998) and has proved to be valuable in analyzing many MLST data sets.

MLST can be used for the detection of foodborne pathogens, by following below steps:1. PCR of given sample using primers specifically for housekeep-

ing genes.2. Run PCR-amplified products on a 1.5% agarose gel.3. Purification of PCR-amplified products.4. Quantification of PCR-amplified products.5. Sequencing of PCR-amplified products.6. Comparison with available MLST database.

MLST is highly unambiguous and portable. Materials required for ST determination can be exchanged between laboratories. Primer sequences and protocols can be accessed electronically (Feil & Spratt, 2001). It is reproducible and scalable. MLST is automated, combines advances in high-throughput sequencing and bioinformatics with established population genetics tech-niques. MLST provides good discriminatory power to differenti-ate isolates.

4.5 Ligase chain reactionLigase chain reaction (LCR) has evolved as a very promising

diagnostic technique that is often utilized in conjunction with a primary PCR amplification for detection of genetic disorders and various pathogens/viruses (Erlich, Gelfand, & Sninsky, 1991). The beginning of LCR can be traced back to pioneering work by Whiteley et al. (1989), who described an oligonucleotide probe-based assay using two probes that are ligated together by thermostable enzyme only when they hybridize to target sequence to immedi-ate adjacent site. Later on, Wu and Wallace in 1989, introduced another version called Ligase amplification reaction (LAR), which employs two sets of complementary primers and repeated cycles of denaturation (at 100°C) and ligation (at 30°C) using the meso-philic T4 DNA ligase. Use of mesophilic, that is, T4 or E. coli, ligase (Modrich et al., 1973) has the drawback of requiring the addition of fresh ligase after each denaturation step, as well as appearance of target independent ligation products (Barringer, Orgel, Wahl, & Gingeras, 1990; Wu & Wallace, 1989). However, LCR appears to be

http://www.mlst.net

http://www.mlst.net


advanced version of LAR as it provides a much higher sensitivity and is less susceptibility to false-positive ligation products.

LCR employs a thermostable ligase to allow amplification of DNA and discrimination of a single-base mutation (Barany, 1991a; Barany, 1991b) using two set of primers (a-b & c-d) having unique sequences in such a way that both sets hybridize to complemen-tary sequences adjacent to each other at target strands as shown in Fig. 5.16 Thermostable ligase minimizes target-independent

Figure 5.16. Ligase chain reaction revealing repeating cycles of product amplification through primer annealing and ligation steps.


ligation because the reaction can be performed at or near the melting temperature (T

m) of the oligonucleotides (Barany, 1991b).

Furthermore, the use of thermostable ligase avoids the need to add fresh ligase after each denaturation step as required in LAR.

As shown in Fig. 5.16, the junction of the two primers (“a” with “b,” & “c” with “d”) is usually positioned so that the nucleotide at the 3′ end of the upstream primer “a” coincides with 5′ phos-phate end of the downstream primer “b” at target. If there is a single base-pair difference at this junction site due to two differ-ent alleles, species, or other polymorphisms correlated to a given phenotype, the two adjoining primers (“a” with “b,” & “c” with “d”) will not be covalently ligated.

DNA ligase uses either an ATP (T4 enzyme) or NAD (E. coli enzyme) cofactor to join covalently the adjacent 3′ hydroxyl and 5′ phosphoryl termini of nucleotides that are perfectly hydrogen bonded to a complementary strand.

The unique feature of LCR is the second set (“c,” “d”) of primers having almost entire sequence complementarity to the first pair (“a,” “b”) designed to have differences in nucleotides at the 3′ end of the upstream primer. In a cycling reaction, using a thermosta-ble DNA ligase, both ligated products can then serve as templates for the next reaction cycle, leading to an exponential amplification process analogous to PCR amplification. As mentioned earlier, if there is a mismatch at the primer junction, it will be discriminated against by thermostable ligase and the primers will not be ligated. The absence of the ligated product therefore indicates at least a single base-pair change in the target sequence (Barany, 1991a).

The greatest potential for LCR amplification and detection is its compatibility with a primary amplification of DNA or RNA by PCR. However, the accuracy of results depends on reaction con-ditions and primer designing. The T

m of all LCR primers should

be within a narrow temperature range, ideally with an absolute T

m of 70 ± 2°C. One primer should not serve as a bridging tem-

plate for other primers; it may result in target-independent liga-tion. 3′ end ligation can be prevented by adding two nucleotides as noncomplementary tails or longer to the nonadjacent 5′ ends of the primers. Different amounts of ligation products depending on the discriminated nucleotides have been observed with a mis-matched target (Barany, 1991a). Ligation efficiency is influenced by the nature of the base pair at the 3′ end of the primer with the matched target. Two sets of LCR primers with the corresponding difference at the 3′ end of the discriminating primer were used for the detection of a single base-pair difference (D128G) in the two alleles of the bovine CD 18 gene (Batt, Wagner, Wiedmann, Luo, & Gilbert, 1994). The study showed that hydrogen bonding of the


G-C base-pairing facilitates a more stable hybrid as compared with A-T base-pairing, therefore allowing a more efficient ligation.

LCR products can be detected using p32 radioactive detection method at 3′ end of the upstream primer (Barany, 1991a, 1991b), fluorescently labeled primers (Feero et al., 1993; Winn-Deen & lovannisci, 1991), digoxigenin, a hapten molecule, labeled RNA primer (Kalin, Shephard, & Candrian, 1992), poly(dT)-coated paramagnetic iron beads (Zebala & Barany, 1993), etc.

The potential of LCR technique has been proven for the identifi-cation and detection of different foodborne pathogens (Wiedmann et al., 1993). This method can be utilized for pathogen detection by applying primers specific to 16S rDNA, encoding part of the ribo-somal DNA as it consists of highly conserved region. LCR primer for 16S rDNA region of different pathogen will label with different fluorescent dyes and after completion of cycle, the products will separate through gel electrophoresis and place for screening.

4.6 MicroarraysModern-day two-dimensional hybridization microarrays were

developed in the 1990s (Shalon, Smith, & Brown, 1996; Schena, 1995). A microarray is a miniaturized device that uses solid sub-strate contains short (25–70-mer) single-stranded DNA oligo-nucleotide probes attached to it (Fig. 5.17). It is also called as gene chip (DNA chip or biochip), which is a collection of micro-scopic DNA spots attached to a microscopic slide fabricated to do genotyping of multiple genomes or to monitor/measure the expression of large numbers of genes simultaneously. DNA micro-arrays are created by spotting thousands of known specific gene sequences from the available database on a single microscopic slide by using robotic machines, mechanical deposition (Schena, Shalon, & Brown, 1995) sprayed on with a modified inkjet printer head (Hughes, Mao, & Jones, 2001) or synthesized in situ through a series of photocatalyzed reactions (Pease, Solas, & Fodor, 1994). Each spot contains picomoles of a specific DNA sequence, which may be a short section of a gene or other DNA elements that are used as probes to hybridize a cDNA or RNA sample under stringent conditions. cDNA is synthesized from RNA isolated from desired samples via reverse transcription. Generally, key phenomenon behind the genotyping is to monitor the change in expression of certain genes, whose increased translation will lead to increased mRNA and hence cDNA (since cellular machinery begins copying certain segments if the gene is activated). Increase and decrease in the expression are directly proportional to the intensity of fluo-rescence of the spot.

Figure 5.17. DNA microarray for food pathogen detection: (A) Synthesis of Cy 3 labeled cDNA from test sample and (B) hybridization of Cy3 labeled cDNA to microchip under stringent conditions, showing each spot on an array associated with a conserved gene sequence of a particular pathogen. The location of the fluorescent signal obtained will show the type of the pathogen present in test sample, and (C) single-stranded DNA oligo probes attached to substrate, with fluorescently labeled (green) target DNA strands bound to selected oligos (McLoughlin, 2011, © Oxford University Press, 2011).


The density of spots on the array may vary from 20,000 spots per slide for a typical spotted array, to several million for platforms, for example, NimbleGen and Affymetrix that use in situ synthesized oligos. Arrays may have subdivided gasket into subarrays, which may allow multiple samples to be tested on one slide. Replicate features, scattered randomly across the array, may also be used to allow correction for scratches and spatial effects. Threshold level of background noise correction can be achieved by including negative control probes with random sequences. Fig. 5.17 gives the detailed schematic to detect the foodborne pathogens using DNA microarrays. As a basic microarray, to screen the presence of food pathogen first step is to collect the messenger RNA molecule from the sample. This mRNA would be then used for synthesis of cDNA using reverse transcription labeled with fluorescent label. This labeled cDNA is then placed onto the DNA microarray slide for hybridization. The labeled cDNAs that represent mRNAs in the cell will then hybridize or bind to their synthetic cDNAs attached on the microarray slide, leaving its fluorescent tag. Then via spe-cial “reader” or “scanner” consisting of some laser, microscope, and camera, the slide is scanned to measure the binding through fluorescent signal for each spot. Then laser-excited fluorescent tags, microscope, and camera work together to create a digital image of array. The data are then stored in a computer, and a spe-cial program is used to calculate the fluorescence for each spot by analyzing the digital image of the array (Fig. 5.17A,B). This is worth mentioning that Miller and Tang (2009) and McLoughlin (2011) have attempted compilation of almost all relevant information about microarrays based on designing method, array design, and analysis. Following are the important details that explain types of microarrays for detection of microbes.

Microbial detection arrays until last decade were thought to occupy a middle ground between low cost, narrowly focused assays such as multiplex PCR and more expensive, broad- spec-trum technologies like high-throughput sequencing. Largely due to advances in fabrication, robotics, and bioinformatics, microar-ray technology has continued to improve in terms of efficiency, discriminatory power, reproducibility, sensitivity, and specificity. Microarrays reported by various groups differ by probe design-ing strategy, type of array platform/substrate, and analysis algo-rithm or method for probe analysis/target detection. Examples of array designs are: (1) ViroChip-first microarray designed for detection of a wide range of pathogen; (2) Resequencing patho-gen microarrays; (3) Universal detection array; (4) GreeneChip; and (5) Lawrence Livermore microbial detection array. Examples of array analysis are (2) GreeneLAMP, (2) E-Predict, (3) VIPR (Viral


Identification using a PRobabilistic algorithm) (4) DetectiV, (5) PhyloDetect, and (6) Composite Likelihood Maximization.

Present-day microarrays include not only 2D arrays but also 3D arrays or suspension bead arrays that has allowed microbial detection for clinical applications. Therefore, various methods/strategies for micro array fabrication are:1. Printed microarrays: These are the oldest/first version of mi-

croarrays utilized in laboratories, which are relatively simple and inexpensive and are fabricated by “printing” or spotting of the probes onto the microarray surface (most commonly a glass microscope slide). Fig. 5.18 explains in brief about print-ed microarrays.

The nucleic acid probe spots, or features, are prepared via ei-ther noncontact or contact printing to create an array of 100- to 150-µm features and possess lower density (i.e., 10,000 to 30,000 features). Size of probes may vary from oligos to small genes, that is, 25–150 bases or 200–800 bases. These microar-rays are relatively simple and inexpensive, providing flexibility as per requirement. However, fabrication of printed microarray process requires costly facilities/setup and requires dedicated space with controlled environmental variables such as dust, humidity and temperature. Microbial diagnosis using printing microarrays needs difficult and expensive tasks of monitor-ing production reproducibility, performing clinical validation studies, and continuous assessment of quality of downstream

Figure 5.18. Printed microarrays are made up of PCR-amplified probes (or oligonucleotides are synthesized) spotted onto a glass slide. Hybridization detection of labeled target nucleic acids (produced via sample processing for RNA extraction, cDNA production, and differential fluorescent labeling) is performed via fluorescent scanning and data analysis (Ehrenreich, 2006, Fig. 5.1A, © Springer-Verlag 2006).


data. An additional barrier is manufacturing, which needs enormous scale of amplicon production and associated diffi-culties of quality control, information management, efficien-cy, and accuracy. Entire process of design of oligonucleotide probes is labor-intensive, and error prone. These can be used for microorganisms, which are still not sequenced completely. These microarrays possess immense potential to be utilized for routine microbial detection that may bring transformation provided these are made commercially available to the users.

2. In Situ-synthesized oligonucleotide microarrays: GeneChips (Affymetrix, Santa Clara, CA), Roche NimbleGen (Madison, WI), and Agilent Technologies (Palo Alto, CA) are examples of available high density microarrays. GeneChips (Affymetrix, Santa Clara, CA, (Fig. 5.19A) are the most widely known in situ synthesized extremely high-density microarrays using semi-conductor-based photochemical synthesis (Fodor et al., 1991). In situ probe synthesis is accomplished through the cycling of masking, light exposure, and addition of either A, C, T, or G bases to the growing oligonucleotide (Dalma-Weiszhausz, Warrington, Tanimoto, & Miyada, 2006; Ehrenreich, 2006). It can be seen from Fig. 5.19A that in Photolithography, UV light is passed through a lithographic mask that acts as a filter to ei-ther transmit or block the light from the chemically protected microarray surface (wafer). In chemical synthesis cycle, UV light removes the protecting groups (squares) from the array surface, allowing the addition of a single-protected nucleotide as it is washed over the microarray. Sequential rounds of light deprotection, changes in the filtering patterns of the masks, and single nucleotide additions form microarray features with specific 25-bp probes. The sequential application of specific lithographic masks determines the order of sequence synthesis on the wafer surface. In this type of microarray, the oligonucle-otide probes (size 20–25 bp or longer) are synthesized directly on the surface of the microarray, on quartz wafer size 1.2-cm2. Small-sized multiple target probes improve sensitivity, speci-ficity, and statistical accuracy of microarray. As a thumb rule, 11 probes are used per 600 bp length along with one base mis-match and mismatch probes acting as negative control. Af-fymetrix GeneChips typically have >106 features per microar-ray depending on the interfeature distance.

Roche NimbleGen (Madison, WI) and Agilent Technologies (Palo Alto, CA) make use of longer nucleotides (60–100 b) grown on respective substrates using maskless photo-mediated synthesis and inkjet technology, respectively, and hence allowing higher sensitivity. Both of them allow multiple color hybridizations. As

Figure 5.19. In situ synthesized oligonucleotide microarrays: (A) Affymetrix GeneChip oligonucleotide microarray showing Photolithography and chemical synthesis cycle (as adapted from Miller & Tang, 2009,); (B) Roche NimbleGen oligonucleotide microarray (as adapted from © Roche NimbleGen, Inc.), and (C) Agilent oligonucleotide microarray (as adapted from © Agilent technology).


shown in Fig. 5.19B, during Roche Nimble Gen microarray fab-rication virtual masks is created using digital micromirror de-vice (DMD) that forms the UV light pattern to direct the specific nucleic acid addition during photo-mediated synthesis. Pho-tolabile protecting group (circles) are removed by UV light and allows addition of a single protected nucleotide to the growing oligonucleotide chain. Oligonucleotide chain length of 60–100 bases length is synthesized through cycling of DMD filtering, light de-protection, and nucleotide addition. Each Nimble-Gen microarray can contain 106 features and can be purchased in the following formats per slide: 1 × 2.1 million features, 3 × 720,000 features, 1 × 385,000 features, 4 × 72,000 features, and 12 × 135,000 features.

Agilent Technology microarray in situ fabrication is shown in Fig. 5.19C (i-iv) where pictorial representation describes print-ing of first layer of nucleotides on the microarray surface us-ing noncontact inkjet printing (delivers a small and accurate volume in picoliters), base-by-base primer extension through repetitive cycles finally leading to final 60-mer in situ-synthe-sized probe on a microarray containing thousands of specific and simultaneously synthesized probes. Agilent microarrays are available in the following formats: 1 × 244,000 features, 2 × 105,000 features, 4 × 44,000 features, and 8 × 15,000 fea-tures. On a comparative note, Affimetrix-based GeneChips platform are impractical to be implemented for microbial di-agnostics despite the fact that resequencing microarrays have been developed by TessArae (Potomac Falls, VA) on this plat-form. This is majorly due to inflexibility and no available cus-tomization availability (Lin et al., 2007; Lin, Malanoski, Wang, & Stenger, 2009). However, Nimblegen and Agilent offer cus-tomization. Agilent even offers web-based tool (eArray) for customization. Although, these methods are expensive they of-fer advantages of reproducibility of the manufacturing process and the standardization of reagents, instrumentation, and data analysis with improved accuracy and reproducibility (Kreil, Russell, & Russell, 2006).

3. High-Density Bead Arrays: Illumina, San Diego, CA have made available Bead arrays where a patterned substrate for the high-density detection of target nucleic acids arranged on 3-µm sil-ica beads randomly self-assembled onto one of two available substrates: the Sentrix Array Matrix (SAM) or the Sentrix Bead Chip (Fan et al., 2005, 2006; Oliphant, Barker, Stuelpnagel, & Chee, 2002). As shown in Fig. 5.20, the SAM contains 96 1.4-mm fiber-optic bundles (bottom left). Each bundle consists of an individual array made up of 50,000 five-micrometer fiber-optic


strands, chemically etched to create microwell for single bead (top left). The Sentrix Bead Chips can assay 1 to 16 samples at a time on a silicon slide (bottom right) processed to provide mi-crowells for individual beads (top right). Both BeadArray plat-forms rely on 3-µm silica beads that randomly self-assemble (center) (Fan, Hu, Craumer, & Barker, 2005). BeadArrays can support up to 105 to 106 features and have built-in redundancy. Analysis tools till date are lagging for available for BeadArray-specific data analysis, background correction, and spatial ar-tifact recognition and they have not been shown for detection of microbes till now except DNA methylation studies, gene ex-pression profiling, SNPs genotyping, etc.

4. Suspension bead arrays: This technology is based on suspen-sion-bead-based assays were initially described in 1977, which was then focused on the detection of antigens and antibod-ies (Horan & Wheeless, 1977). Red (658-nm emission) and infrared (712-nm emission) fluorochromes are used at vari-ous concentrations to fill 5.6-µm microspheres. As shown in Fig. 5.21, each bead consists of the 100-microsphere set with unique spectral address (i.e., red-to-infrared ratio) is coupled to a specific probe, which functions equivalent to a feature in a planar microarray. Different microspheres coupled to multiple probes (generally up to 100 types/beads) are used to detect

Figure 5.20. Schematic of high density bead array (Fan et. al., 2005).


extracted target nucleic acids (preamplified and denatured). Microspheres 5.6 µm in diameter (filled with different relative concentrations of an infrared dye and a red dye) to achieve unique spectral identity. Fig. 5.21 explains potential targets that are amplified using a biotinylated primer and then denatured and hybridized to microspheres tagged with target-specific se-quence probes. Probe-target hybridization is measured using a streptavidin-bound green fluorophore. Fig. 5.21 contains flow cytometry analysis to analyze the microsphere suspension. Probe is analyzed through red laser to determine the spectral identity of the bead. Then quantification of probe- target reac-tion on microsphere surface is carried out by exciting reporter fluorochrome by a green laser. Very much like ELISA, reporter probes, that is indirect hybridization (Armstrong, Stewart, & Mazumder, 2000; Spiro, Lowe, & Brown, 2000) and competi-tive assays (Dunbar, 2006) have also been reported where the presence of fluorescence indicates the absence of target DNA hybridization.

This method is the most practical form of microarray that can be implemented for clinical diagnosis of microbes despite the fact that the feature density of suspension bead arrays is

Figure 5.21. Suspension Bead Arrays (As adapted from Dunbar, 2006).


the lowest of all the platforms. Availability of various beads makes it the most flexible method. In 2008, FDA approved infectious-disease suspension bead array (xTAG RVP), which detects 12 respiratory viruses, and subtypes were brought to the market by Luminex (Krunic et al., 2007; Merante, Yaghou-bian, & Janeczko, 2007). This method is relatively simple, af-fordable bead array suspensions and easy in multiplexing to warrant its potential for high throughput nucleic acid detec-tion for microbial detection. Only cons appear to use con-tamination control measures and can be used only after PCR amplification.

5. Electronic microarrays: NanoChip 400; Nanogen, San Diego, CA have developed this using complementary metal oxide semiconductor technology for electronic microarrays that uses active hybridization via electric fields to control nucleic acid transport. Fig. 5.22 describes the detailed fabrication of elec-tronic array. Fig. 5.22A shows that when a positive electric cur-rent is applied to test sites, it facilitates the active movement and concentration of negatively charged biotinylated DNA probes to the activated (streptavidin containing) locations. Once the

Figure 5.22. Electronic microarrays. Here P1, parainfluenza virus type 1; P2, parainfluenza virus type 2; P3, parainfluenza virus type 3; FB, influenza B virus; FA, influenza A virus; RSV, respiratory syncytial virus; BKGD, background. (as adapted from Miller & Tang, 2009).


first probe is bound to its targeted location(s) by streptavidin-biotin bonds, the test site(s) can be deactivated, and current can be applied to a different test site to bind another set of probe. This process is repeated until all the different probes are arrayed (Fig. 5.22B). Fig. 5.22C explains commercially available Nanogen’s RVA ASR where upon application of the probes to targeted test sites, extracted, and amplified nucleic acids from a respiratory sample passively hybridize to the microarray surface. If hybridization occurs, secondary probes specific for target but nonspecific to detector sequence will bind. Second-ary probes (fluorescent detector oligonucleotides) are used to measure positive hybridization reactions. Multiple probes can be used per site when multiple fluorophores are incorporated. This electronic microarray offers multiplex detection even at an individual test site using multiple probes with a distinct flu-orophore through sequential measurement. The system also offers flexibility for the detection of multiple targets, or nucle-ic acids from multiple samples minimizing waste and allows more flexibility in assay design and decreases costs associated with microarray manufacturing. Electronic microarrays den-sity is limited to 400 spots, which is still sufficient for microbial detection applications. In 2007, Nanogen announced the ter-mination of its microarray business; despite the fact that it was good demonstration of the evolution of microarray technology to a platform especially for diagnostic applications.

Detection of bacterial pathogens is often demonstrated using com-bination of PCR and microarray-based assay (Järvinen et al., 2009). In this method, the broad-range PCR primer mixture was designed using conserved regions of the bacterial topoisomerase genes gyrB and parE and Methicillin resistance (mec A) rather than 16 sRNA gene. These modified broad- range PCR primers and probes, sin-gle or even multiple infection-causing bacteria, could be simulta-neously detected and identified. The bacterial pathogen panel of the assay covered the following species: Acinetobacter baumannii, Enterococcus faecalis, Enterococcus faecium, Haemophilus influ-enzae, Klebsiella pneumoniae, Listeria monocytogenes, Neisseria meningitidis, Staphylococcus aureus, Staphylococcus epidermidis, Streptococcus agalactiae, Streptococcus pneumoniae, Streptococcus pyogenes, and selected coagulase-negative staphylococci (CNS) species. The primer design allowed the use of a novel DNA ampli-fication method, which produced labeled, single-stranded DNA suitable for microarray hybridization. ArrayTube microarray plat-form was demonstrated to detect and identify bacterial pathogens with a high degree of sensitivity, differentiate between various


pathotypes of the same bacterial species, and to be capable of detecting antimicrobial resistance genes from an isolated DNA sample. The feasibility of this assay in routine diagnostic testing was evaluated and demonstrated for 146 blood culture positive and 40 blood culture negative samples.

Microarrays are also reported with multiplex PCR amplifica-tion for the simultaneous detection and identification of a panel of microbial pathogens in a single reaction (Khodakov et al., 2008), detection, and identification of enteropathogenic bacteria at the species and subspecies levels, covering pathogenic Escherichia coli, Vibrio cholerae, Vibrio parahaemolyticus, Salmonella enterica, Campylobacter jejuni, Shigella spp., Yersinia enterocolitica, and Listeria mono-cytogenes (You et al., 2008). In addition to this, Boving et al. reported multiplex PCR with product detection by the Luminex suspension array system covering Neisseria menin-gitidis, Streptococcus pneumoniae, E. coli, Staphylococcus aureus, L. monocytogenes, Streptococcus agalactiae, herpes simplex virus types 1 and 2, and varicella zoster virus directly from cerebro-spinal fluid (Bøving, Pedersen, & Moller, 2009). A panel of bacte-rial pathogens was detected using ResPlex I mircroarray system, manufactured by Qiagen (Valencia, CA) for pneumonia in chil-dren (Deng et al., 2009). Microarrays are reported for applications such as Host Genomic Polymorphism Determination, Microbial Gene Expression Profiling, Host Gene Expression Profiling dur-ing Microbial Infections, Microbial Typing, and Determination of Antimicrobial Drug Resistance. Among these, microbial detec-tion and identification is one of the important application, which needs focused attention for development of newer and focused customized versions.

Recent reports also state that microarrays have become inher-ently parallel devices that have offered non-PCR-based alternative with the ease of limited level of efforts for determining desired site of interest for various individual genotypes and use of automated statistical methods that significantly improve their performance (Fodor et al., 1991; Pease et al., 1994). For this purpose, Variation Detection Arrays (VDAs) manufactured by Affymetrix microar-ray were reported to have success with 12% and 45% of false detection of variants (Cargill et al., 1999; Halushka et al., 1999; Wang et al., 1998) indicating average accuracy of about 99.99% and 99.93%. Cutler et al. have developed an automated statisti-cal method (ABACUS-Adaptive Background genotype Calling Scheme) and have demonstrated its use for Affymetrix variation detection arrays (VSAs) in microarray hybridization data. They successfully established the method to accuracy of single nucleo-tide polymorphism (SNPs) for 32 autosomal and eight X-linked


genome regions spanning 50–100 kb region in 40 humans experi-mentally as well as electronically with almost 99.9999% accuracy instead of >80% of genotype calls on a VDA [Cutler et al., 2001]. This method constructed an objective statistical framework to distinguish genotype calls that can be made with extraordinary accuracy from those less reliable ones. Quality score is assigned to each VDA genotype cell while using phred scores in conjunction with other neighborhood quality rules so that sites with extraordi-nary high confidence can be distinguished from less reliable ones for both haploid and diploid targets through application of sta-tistical method–ABACUS algorithm. Therefore, researchers might employ this critical piece of information in different experiments in a variety of fashions. ABACUS combined with Affymetrix VDAs appears to be a technology that can facilitate high-throughput variation detection and genotyping of relatively large genomic regions.

5 Genotyping methods for detection of foodborne pathogens5.1 Pulse field gel electrophoresis

Pulse Field Gel Electrophoresis (PFGE) is the method devel-oped for separation of large DNA molecules. In conventional DNA electrophoresis, a constant electrical field is applied across a block of agarose gel and small DNA molecules are “sieved” in a size- dependent manner. However, the sieving effect underly-ing such separations fails when very large DNA molecules have to be resolved. DNA molecules above a certain size limit migrate together, regardless of length (i.e., large DNA molecules migrate abnormally fast) due to formation of ball-like random coils that can electrophorese through much smaller gel pores. DNA mol-ecules/coils can only be electrophoresed after unravelling to enable threading or reptation through a gel matrix. PFGE provides a way to solve these problems for separation of larger DNA mol-ecules (∼ 12 Mb size) in agarose gels (Orbach, Vollrath, Davis, & Yanofsky, 1988).

PFGE was first described by Schwartz and Cantorto to get size-dependent electrophoretic separations (avoiding molecular siev-ing effect) of very large DNA molecules. PFGE effect utilizes the reptation phenomena through abrupt electrical perturbations to the paths of reptating DNA threads through a gel. Direction of electrical field is periodically altered, to provide larger sized mol-ecules to assume new orientations. Generally, larger the DNA size,


longer is time required for reorientation and then DNA separates with maximum electrophoretic mobility. Therefore, the net elec-trophoretic mobility strongly depends on the size of the DNA and frequency of the applied electrical fields. Consequently, as mole-cules reorient, they more effectively reptate through the gel matrix with lesser size dependence. Following are some factors that affect the limit of resolution of PFGE:1. The uniformity of the two electric fields2. The duration of the electric pulses3. The ratio of the pulse time for each of the alternating electric

fields4. The angles of the two electric fields to the gel5. The ratio of the strengths of the two electric fieldsPFGE is currently used by the Nebraska Public Health Laboratory (NPHL) for molecular epidemiology of foodborne and nosoco-mial pathogens (Fey, NPHL report). As larger sized molecules can be separated, PFGE can be used for molecular analysis to study the genes and genomes for microbes, mammalian cells, large insert cloning system-like yeast (Lim et al., 2001; Schwartz & Cantor, 1984). For some organisms, intact chromosomes can be separated from each other by PFGE for gene mapping studies using Southern hybridization and providing a source of purified chromosomal DNA. Application of PFGE can reveal chromosome length polymorphisms to facilitate evolutionary and population studies. Long-range maps up to thousands of Kb (kilobases) can be constructed for chromosomal DNA that is too large (i.e., above 12 Mb size) using PFGE with traditional restriction and deletion mapping techniques.

As shown in Fig. 5.23, PFGE generally starts with the restric-tion digestion of large genomic DNA fragments with a restriction enzyme; this digestion yields several linear molecules of chromo-somal DNA. After digestion of DNA, the sample loaded to agarose gel is separated using PFGE. As per the requirement, DNA loaded in the gel can be exposed to opposing electric fields either in two or more distinct directions for the DNA molecules.

Figure 5.23. Pulse field gel electrophoresis.


The electric field reorientation angle applied to the agarose gel at the desired time interval for next 12–14 hours to separate DNA can be visualized for the generated banding pattern by soaking in EtBr solution (staining dye). The results can be analyzed as fol-lows: when the DNA banding pattern is same, that is two different samples contain same restriction sites, both samples are consid-ered as the same sample. Whereas, when the DNA banding pattern is different, it shows that the sites at which the restriction enzymes acted on the DNA are different and therefore considered different samples. Recently, PFGE has been reported to be as a gold stan-dard methods for bacterial typing and identification (Neoh et. al, 2019).

5.2 Rapid amplified polymorphic DNARandom Amplification of Polymorphic DNA (RAPD) is a PCR-

based molecular technique used to study the polymorphic pat-tern of DNA. In this technique, segments of DNA are amplified with the help of specially designed primers for the given DNA sample using PCR. Primers for RAPD are designed with arbi-trary sequence such that random and unknown DNA targets are amplified. Generally, a short computer-generated polymorphic (occurring more than once) primer consisting of 8–12 nucleo-tides sequence is selected to have better probability to bind and amplify the DNA regions. However, no prior knowledge of the target sequence is required for RAPD reaction as the primers will bind somewhere in the sequence and on resolving the gel pat-tern, a semiunique profile can be gleaned. RAPD in the terms of discriminatory power is equivalent to that of PFGE, less costly, and relatively fast. RAPD is also referred to as arbitrarily primed PCR (AP-PCR) analysis, which is a rapid and valuable technique for distinguishing different strains of same species (Lawrence, Harvey, & Gilmour, 1993) with a high level of strain discrimination (Lawrence & Gilmour, 1995). It is particularly a very useful tech-nique for genetic typing of human pathogens from foods, process-ing plants, and foodborne outbreaks. In addition, RAPD is such a powerful method that can efficiently replace cumbersome typing methods like serotyping, ribotyping, multilocus enzyme electro-phoresis, restriction enzyme analysis, and phage typing (Boerlin, Bannerman, Ischer, Rocurt, & Bille, 1995). RAPD is also capable of distinguishing strains of a given species with identical 16S rDNA sequences (Czajka et al., 1993). This high level of discrimination can allow RAPD to be used in establishing the persistence of a spe-cific strain in foods or processing plants and its distinction from transient strains of the same species.


As mentioned in Section 3.1, PCR employs two primers for DNA amplification, these primers are highly specific for the target sequence and occurs only once (monomorphic) in the genomic DNA of the organism. However, a single random primer is used for RAPD for which no specific target sequence is known that binds randomly at unknown sites of genomic DNA. The amplification in subsequent cycles depends on positions of primer binding site at complementary strand. If primers annealed too far apart or 3′ ends of the primers are not oriented (facing) each other, amplified fragment will not be generated. If the primers are closely located in the subsequent cycles, a number of different target sequences will be amplified, resulting in a characteristic DNA banding pat-tern for each culture. Conventional PCR has primers designed specially to amplify region or gene of interest and after first cycle, four target sequences are available for duplication (Fig. 5.4). As shown in Fig. 5.24 (a), DNA fragment contains three genes (gene A, gene B and gene C) and gene B is the gene of interest to be ampli-fied. Two primers will select to anneal at each end of gene B spe-cifically. After PCR cycles, amplified fragments of gene B will be generated, which can be processed for further analysis. However, for RAPD, Fig. 5.24 (b) whole genome or a large fragment of DNA is used as the template in a PCR reaction containing many copies of a single arbitrary primer. If primers anneal to complimentary sites 1, 2, 3, 4, 5, and 6 present on the template strand, only two products A and B will be formed. Product A by PCR amplification of the DNA sequence, which lies in between the primers bound at positions 1 and 4, and product B are produced by the primers bound at positions 2 and 5. No PCR product by the primers 3 and 6 because these primers are too far apart to allow completion of the PCR reaction and also by primers at position 4 and 2 or 5 and 3 because these primer pairs are not oriented toward each other.

5.3 Restriction fragment length polymorphismRestriction Fragment Length Polymorphism (RFLP) is a molec-

ular technique developed for genetic analysis, which is based on unique patterns of sites for “restriction nucleases” or “molecular

Figure 5.24. Conventional PCR versus RAPD amplification.


scissors.” Restriction nucleases are class of enzymes that cut DNA molecules at specific sequence/regions. Each enzyme recognizes a unique sequence (4-6 bp long) of nucleotides in the DNA strands. These sequences are palindromic, that is the complimentary DNA strand has the same sequence in the reverse direction such that both strands of DNA are cut at the same location. The generated DNA fragments are separated via agarose gel electrophoresis to determine the number of fragments and their relative sizes. The term “polymorphism” refers to the slight phenotypic/genotypic differences between individuals that arise due to slight differ-ence in base pair sequences of common genes. Even though all members of a species have essentially the same genetic makeup, these slight differences account for variations in phenotype (i.e., appearance, metabolism, etc.) between individuals. The pattern of fragment sizes will be characteristic for each individual tested. RFLP is among one of the important techniques used by forensic scientists for DNA fingerprinting. It is also used for tracing ances-try, studying evolution and migration of wildlife, and detection/diagnosis of certain diseases.

Fig. 5.25 shows steps involved in RFLP analysis. First step uti-lizes one or more restriction enzyme to cut the DNA molecule into small fragments. Generated double-stranded (ds) DNA fragments are then separated using agarose gel electrophoresis. The sepa-rated DNA fragments are denatured and transferred to a nitrocel-lulose membrane (i.e., through a process of southern blotting).

Figure 5.25. Restriction fragment length polymorphism.


Blot is then removed and hybridized with radio-labeled specific DNA probe. This hybridized blot is exposed to X-ray film to detect the banding pattern, which is unique for every individual. An RFLP occurs when the length of a detected fragment varies between individuals. Each fragment length is considered an allele, and can be used in genetic analysis.

5.4 Amplified fragment length polymorphismAmplified Fragment Length Polymorphism is a PCR-based

DNA fingerprinting technique developed in the early 1990s by Keygene but originally described by Zabeau and Vos in 1993. The whole process of AFLP consists of three major steps as shown in Fig. 5.26.1. Restriction digestion of target molecule and ligation of adapter

molecules2. Selective amplification of some of these fragments with the

help of two PCR primers that have sequence corresponding to adaptor and restriction site-specific sequences

3. Electrophoretic separation and visualization of amplified frag-ments through autoradiography or fluorescence methodologies

AFLP is a highly sensitive method for detecting polymorphisms in DNA. PCR amplification of restriction fragments is achieved using the adapter and restriction site sequence as target sites

Figure 5.26. Amplified fragment length polymorphism.


for primer annealing. The selective amplification is achieved by the use of primers that extend into the restriction fragments, amplifying only those fragments in which the primer extensions match the nucleotides flanking the restriction sites. Using this method, sets of restriction fragments may be visualized by PCR without knowledge of nucleotide sequence. The method allows the specific coamplification of high numbers of restriction frag-ments. The number of fragments that can be analyzed simulta-neously, however, is dependent on the resolution of the detection system. Typically 50–100 restriction fragments are amplified and detected on denaturing polyacrylamide gels (Vos et al., 1995). Additionally, the power of AFLP is that it does not require prior information regarding the targeted genome, as well as in its high reproducibility and sensitivity for detecting polymorphism at the level of DNA sequence. for plant and microbial studies (Pawn and Schönswetter, 2012). This method is also helpful in assessing genetic diversity within species or among closely related species.

5.5 RibotypingRibotyping is a method used for the identification and classifi-

cation of microbial genera, from fungi to bacteria, on the basis of differences in rRNA (ribosomal RNA) structural gene sequences. The molecular genetic basis of ribotyping is the sequence of ribo-somal operon, where each operon consists of three genes encod-ing the structural rRNA molecules, 16S, 23S, and 5S, known as polycistronic operon. Almost all the microbial organisms consist of some highly conserved regions in their genome in the form of copy numbers, overall ribosomal operon sizes, nucleotide sequences, secondary structures, etc. (Maidak et al., 1997) due to their fundamental role in polypeptide synthesis (Woese, 1996). In bacterial species, 16S rRNA gene is known to be highly conserved region; therefore, it is preferred for ribotyping studies (Kolbert & Persing, 1999; Pace, Olsen, & Woese, 1986; Woese, 1987). Grimont & Grimont, 1986 developed a new approach of bacterial clas-sification based on the 16S rRNA conserved gene sequence (Fox et al., 1980) and basic 16S-23S-5S ribosomal operon structure (Doolittle & Pace, 1971; Gurtler & Stanisich, 1996).

In the conventional ribotyping (Fig. 5.27), the total genomic DNA is digested into discrete-sized fragments using restriction endonucleases followed by electrophoretic separation. These DNA fragments are then processed for southern blot transfer (Southern, 1975) and hybridized with a radiolabeled ribosomal operon probe to reveal the pattern of rRNA genes. Following auto-radiography, bands containing a portion of the ribosomal operon are visualized. The number of fragments generated by ribotyping


is a reflection of the multiplicity of rRNA operons present in a microbial species.

More rapid and practical alternatives have been developed for the clinical microbiology laboratory for identifying bacteria to the species level to discriminate for rigorous intraspecies epidemio-logical differentiation.1. PCR ribotyping: Kostman, Edlind, LiPuma, and Stull (1992),

Kostman et al. (1995) and Gurtler and Barrie (1995) developed a universal approach of PCR ribotyping for the epidemiological discrimination among pathogenic microorganisms. Instead of using radiolabeled probes, they used primers complemen-tary to the 3′ end of the 16S rRNA gene and the 5′end of the 23S rRNA gene, PCR ribotyping reveals length heterogeneity of the PCR-amplified intergenic spacer region (ISR) (Gurtler & Barrie, 1995; Kostman et al., 1995). Although developed for epidemiological analysis and for discrimination of pathogens, PCR ribotyping proved not to be universally applicable (Cart-wright, 1995) due the reason that in some species, ISR length is variable within and between isolates; in others, ISR lengths are limited to one or two sizes, usually dependent on the number of tRNAs present (Christensen, Jorgensen, & Olsen, 1999; Sev-erino, Darini, & Magalhaes, 1999).

2. PCR ribotyping followed by restriction endonuclease subtyp-ing: Ryley, Millar-Jones, Paull, and Weeks (1995) and Shreve, Johnson, Milla, Wielinski, and Regelmann (1997) modified the method of PCR ribotyping followed by restriction digestion of

Figure 5.27. Ribotyping for detection of foodborne pathogens.


amplified product so that subtyping of isolates can be done by amplification of ISRs using PCR to further subtype isolates for which PCR ribotyping was nondiscriminatory. The band pat-tern observed was identical with that observed in conventional ribotyping, and hence proved to be inherently limited.

3. Amplified rRNA gene restriction analysis (ARDRA): Jayarao, Dore, Baumbach, Matthews, and Oliver (1991) develop ARDRA, based on amplification of the 16S rRNA gene and followed by restriction digestion of amplified product for interspecies dif-ferentiation of isolates.

4. Long PCR ribotyping: Smith-Vaughan, Sriprakash, Mathews, and Kemp (1995) developed improved method based on PCR amplification of the entire 16S-23S-5S ribosomal operon fol-lowed by restriction digestion. However, this method has the limitation due to lack of heterogeneity of the ISR in many spe-cies and the known conservation of 16S and 23S rRNA genes, it can be assumed that this technique will require the same cave-ats as PCR ribotyping.

5. Automated ribotyping: Automated ribotyping (AR) provides full automation of the manual steps giving rapidity, high reproduc-ibility, and typeability. AR is a suitable characterization method for some pathogens when the research purpose requires a ge-notyping at strain level within very short span of time (Pavlic & Griffiths, 2009). The systems developed for AR automate all steps in the process from cell lysis to data capture (via a CCD camera, the patterns stored in a digitized format) followed by online data base comparisons among the available databases or libraries.

Genetic variation in housekeeping genes is primarily responsible for ribotype polymorphisms; therefore, it is a key factor for ribo-type RFLPs. Elucidation of the basis of ribotyping at this molec-ular genetics level has to establish its utility and expertise of the user toward the study of bacterial population genetics and species diversity for the detection of foodborne pathogens.

5.6 Denaturing gradient gel electrophoresisDenaturing gradient gel electrophoresis (DGGE) is a modifica-

tion of gel electrophoresis used to separate PCR generated DNA products. PCR of an environmental sample generates a number of templates with different DNA sequence representing micro-bial population present in the sample. For PCR products from a given reaction which are of similar size (200–700 bp), conven-tional separation by agarose gel electrophoresis results only in a single DNA band and is largely non-descriptive. To overcome this limitation, the technique of DGGE has been developed that uti-lizes differential denaturing characteristics of DNA. Therefore,


this method is used to detect non-RFLP polymorphism or single nucleotide changes or small insertions or deletions in DNA based on sequence differences (Myers, Maniatis, & Lerman, 1987). DGGE has been reported frequently for identifying single-nucleotide polymorphisms without the need for DNA sequencing and as a molecular fingerprinting method for complex ecosystem commu-nities, in particular in conjunction with amplification of microbial 16S rRNA genes (Strathdee & Free, 2013).

The small genomic restriction fragments are run on a low to high denaturant gradient acrylamide gel; initially the fragments move according to molecular weight, but as they progress into higher denaturing conditions, each reaches a threshold denatur-ant condition where DNA begins to melt at which time migration slows dramatically, that is mobility shift is observed. Different DNA sequences denature at different concentrations and there-fore generate a pattern of bands representing a different micro-bial population present in the community. Once generated, fingerprints can be uploaded into databases in which fingerprint similarity can be assessed to determine microbial structural dif-ferences between environments or among treatments. The main advantage of DGGE is its sensitivity that can detect virtually all mutations in a given piece of DNA. Because of this, it is often used in genetic screening.

Generally used denaturants are heat (a constant temperature of 60°C) and a fixed ratio of formamide (0%–40%) and urea (0–7 M). Occasionally, an increasing temperature gradient replaces the chemical denaturant gradient and then the process is called tem-perature gradient gel electrophoresis. The denaturation of DNA should start from one end of the duplex of DGGE rather than denaturing in the middle first or at both ends at the same time.

6 DNA sequencing methods for detection of foodborne pathogens6.1 DNA sequencing: technology

The DNA sequencing technique helps biologists to determine the precise order of nucleotide bases (A, G. C, and T), in the DNA strands extracted from biological samples (Kchouk, Gibrat, & Elloumi, 2017). The order of nucleotides is the code to all biologi-cal life forms on earth and can be used to differentiate different species (of plants, animals, or microorganisms) and individu-als within a species. In recent times, DNA sequencing has been extensively adopted by the researchers for its use in the identifi-cation, typing, characterization, and taxonomic classification of unknown or novel pathogens isolates.


In most sequencing techniques, the process involves breaking the DNA of the genome into many smaller pieces that are sequenced using sophisticated instruments called “DNA Sequencers.” The sequenced fragments are assembled into a single long “consen-sus” that is further analyzed using various interpretation software to provide meaningful insights about the organisms’ existence and its interactions with the environment (e.g., detection of SNPs and other variants, Phylogenetic Analysis, Diagnostics). In some others, however, the complete genome can be sequenced at once.

6.1.1 First-generation sequencing methodsFew years ago, Sanger and Maxam-Gilbert sequencing meth-

ods (Kchouk et al., 2017), also known as the “First-Generation Sequencing Methods,” were the most common technologies used by the biologists to directly sequence DNA. They were used to determine the sequences of relatively small fragments of DNA called “Reads,” but the researchers could sequence the entire DNA fragment using “Reads” generated through multiple sequencing cycles. The sequenced “Reads” were then aligned based on over-lapping regions to assemble into sequences of larger regions of DNA and, eventually, entire chromosomes.

6.1.1.1 Maxam–Gilbert sequencingThe Maxam-Gilbert sequencing method was developed by

Allan Maxam and Walter Gilbert in 1976–77, and became the most popular DNA sequencing method as it allowed the use of puri-fied DNA directly for sequencing (Kchouk et al., 2017). It is also Known as “Chemical Sequencing” for the fact that the sequencing method is based on the chemical modification of DNA and subse-quent cleavage of the macromolecule at specific bases.

The sequencing process requires the DNA to be extracted from the biological sample and purified. The purified double-stranded DNA is then labeled at the 5′ end of the DNA with a radioactive iso-tope. Chemicals are used to essentially break the DNA using four different reactions that cleave the DNA specifically at:• a C,• a C or a T• a G• a G or an A

The generated fragments or “Reads,” as they are called, are run on a gel and visualized using X-ray film to read the sequence through electrophoretic separation of “Reads” based on their mobility in the gel.

6.1.1.2 Sanger sequencingAnother technique, known as “Sanger sequencing,” that was

developed by the British biochemist Fred Sanger and his colleagues


in 1977 became the most applied technique of sequencing due to its high efficiency and low radioactivity (Fig. 5.28F) (Kchouk et al., 2017). It is also known as “Chain Termination Method.” The initial Sanger method required cloning for the start of each read. Later, cloning was replaced by PCR amplification of the “Region of Interest or ROI” (region of the DNA molecule to be sequenced) followed by sequencing on highly sophisticated DNA sequencers.

The sequencing process uses special type of synthetic nucle-otides known as ddNTPs, which lack -OH group at 3′ carbon of the ribose sugar. After the target DNA is amplified and purified, a sequencing PCR is performed in four separate sequencing reac-tions, each using either of the primers specific to the target region, Taq Polymerase enzyme, dNTPs, and one of the four labeled ddNTPs. The Taq DNA polymerases cannot distinguish between dNTP and ddNTP and uses both types as its substrates.

During the extension step of the PCR cycle, whenever ddNTP is added to the growing chain, further elongation of the chain will be stopped because incoming dNTP cannot form a phosphodiester bond. Following multiple rounds of template DNA extension from the bound primer, amplified DNA fragments of varied lengths with the fluorescently labeled 3′ end are generated. The resulting DNA fragments are heat denatured and separated by size using gel electrophoresis. In modern DNA sequencers, the basecalling is performed with the help of analysis software that enable more accurate and faster sequencing. Further, the sequenced “Reads” can be aligned with the help of various alignment software avail-able in the research community.

Figure 5.28. Sanger sequencing: (A) Genomic DNA (B) DNA fragmentation resulting in short fragments of up to 900 bp. (C) PCR amplification using primers against targeted regions (D) Addition of DNA Polymerase, dNTPs and ddNTPs to purified product (E) to (G) Sequencing cycles and subsequent detection of the respective fluorescence signal that is generated corresponding to the ddNTP incorporated. (as adapted from Gaurab Karki, 2017)


6.1.2 Next-generation sequencingThe next-generation sequencing technologies (also known

as “High Throughput Sequencing” or “HTS”), first appeared in Roche’s 454 technology in 2005, were very high throughput and cost-effective than the first-generation sequencing technologies (Kchouk et al., 2017).

The newer NGS technologies can sequence millions to billions of “Reads” parallelly in a single run producing GigaBase-sized reads in only a few days or hours. The sequencing of the human genome took many years using the Sanger Sequencing technol-ogy and was done at a very high cost. With the next-generation sequencers, genome sequencing can now be done in just a few months and at a much reduced cost.

The NGS technologies can be classified into two major types:1. The second-generation sequencing technologies, which refer

to the sequencing technologies developed after the first gen-eration and are characterized by the need to prepare “Clones or Clusters” of the sequencing “Reads” through amplification (Karl et al., 2010). They include: Roche 454 Sequencing, Illumina SBS, SOLiD Sequencing, and Ion PGM Sequencing technology.

2. The third-generation sequencing technologies that allow se-quencing a single DNA molecule without the need of amplifi-cation libraries and can generate longer “Reads” at much lower costs and in a shorter time. They include Pacific biosciences SMRT sequencing and Oxford nanopore sequencing.

6.1.2.1 Roche 454Developed by 454 (Fig. 5.29) Life Sciences of Brandford, CT,

USA, the 454 Genome Sequencer instrument was marketed by Roche Applied Science and has been commercially available since 2005 (Kchouk et al., 2017). It is one of the first non-Sanger-based sequencing methods to be available on the market. It uses PCR amplification and pyrosequencing of the query DNA fragments.

Roche 454 sequencing can sequence multiple reads parallelly. The genomic DNA to be sequenced is sheared to generate shorter reads. Generic adaptors are added to the ends of the DNA frag-ments. The DNA fragment is attached to agarose beads, with the help of adapters. This is followed by clonal amplification of the beads through an emulsion PCR, resulting in up to about 10 mil-lion copies of template DNA.

The clonally amplified beads are loaded on a glass fiber slide along with DNA polymerase, primers, and sequencing buffers such that a single well of the glass fibre slide contains one bead. The sequencing begins with the incorporation of dNTPs (A, G, C, or T) on the attached DNA template resulting in the release of a


pyrophosphate molecule. The released pyrophosphate is used for the synthesis of ATP and, subsequently, ATP is utilized to generate a light signal from the luciferase enzyme system. The light signal is recorded by the detector and the corresponding nucleotide base is called. The dNTP mix is then washed away and the process is repeated, cycling through the other dNTPs one by one.

The locations and intensity of the signals are used to determine the specific beads that the base was added to and the number of bases added to them. Specific analysis software available with the DNA Sequencers analyze the acquired signal density sequence to determine the Sequence and align the overlapping “Reads” to generate a consensus. All the sequence reads obtained from 454 are of different lengths because different numbers of bases are added with each cycle.

6.1.2.2 Illumina SBSIllumina Sequencing by Synthesis (SBS) is the most used NGS

technique (Fig. 5.30). Developed by Solexa in 2006, it works on a different principle called reversible terminator nucleotides (Kchouk et al., 2017). The process allows sequencing and detec-tion of hundreds and millions of clusters are sequenced simulta-neously in a massively parallel fashion.

The genomic DNA to be sequenced is fragmented and adapter molecules are added to both ends of generated DNA fragments to construct an Illumina-specific adapter library.

Figure 5.29. Roche 454: (A) Genomic DNA (B) DNA fragmentation and Library construction (C) Clonal Amplification through emulsion PCR (D) Deposition of clonally amplified beads and sequencing enzymes into the well of the glass fibre slide positioned to face the detector (E) & (F) Sequencing cycle and subsequent detection of released pyrophosphate molecule, used for the synthesis of ATP and, subsequently, ATP is utilized to generate a light signal from the luciferase enzyme system when a base is incorporated. (as adapted from Kim, 2012; EBI).


Each fragment molecule is then immobilized on a proprietary flow cell surface and isothermally amplified though the process of “Clustering”. The flow cell is a glass slide with lanes. Each lane is coated with two types of oligos, complimentary to the adapter mol-ecules, which help in the anchoring of the DNA fragments to the flow cell surface. During the library preparation process, additional motifs such as the sequence binding sites, unique indices, and nucleotide regions complimentary to the flow cell oligos are also introduced.

The clustering process begins with the hybridization of the single-stranded DNA fragment to one type of oligo on the flow cell surface. A polymerase creates the compliment of the hybridized strand using the adapter sequence as the primer. The DNA mol-ecule is then denatured and the original template is washed away. The newly synthesized strands, anchored on the flow cell, are clonally amplified through bridge amplification, where the DNA strand is hybridized to the second type of oligo forming a bridge-like structure. The polymerase synthesizes complimentary strand using the second type of oligo as the primer. The bridge is dena-tured resulting in separation of the forward and reverse template strands. The process is repeated over and over again, ultimately generating millions of clusters of each single template molecule in close proximity (diameter of one micron or less)

Figure 5.30. Illumina SBS: (A) Genomic DNA (B) DNA fragmentation and Library construction (C) Clonal Amplification through emulsion PCR (D) Deposition of clonally amplified beads and sequencing enzymes into the well on a flow cell (E) Bridge amplification PCR resulting in generating millions of clusters of each single template molecule in close proximity (F) & (G) Sequencing cycles and subsequent detection of the respective fluorescence signal that generated corresponding to the nucleotide incorporated (as adapted from Kim, 2012, and EBI).


After the bridge amplification, the reverse strands are cleaved and washed off, leaving only the forward “Read 1” strands and the second type of oligo attached to the flow cell surface. The 3′ ends are protected to prevent unwanted priming. The sequencing primers and four reversible terminator-bound dNTPs (A, C, T, G), each having a reversible 3′ terminator and a unique fluorescent label, are introduced on to the flow cell. Sequencing begins by the extension of the “Read 1” sequencing primer by incorporation of the nucleotides. The reversible 3′ blockers force the addition of only one nucleotide at a time, followed by imaging to detect the fluorescence generated at the end of the cycle. The 3′ blockage and the fluorescent dye are then removed from the incorporated nucleotide allowing the next sequencing cycle to begin. Base calls are made directly from signal intensity measurements during each cycle, which greatly reduces raw error rates compared to other technologies. After the completion of the first read, the “Read 1” product is washed away and the 3′ ends of the template are depro-tected. The template then falls over the second oligo and hybrid-izes to generate the reverse “Read 2” strand. The “Read 1” template is then cleaved and washed away leaving only the reverse strand on the flow cell. The sequencing is carried over for the “Read 2” template using “Read 2” primers and following the same steps.

The sequencing process generates millions of reads represent-ing all fragments. Specialized data collection software enables users to analyze the data produced by the sequencing process. During analysis, the sequences are separated based on unique indices introduced during library preparation. For each sample, reads with similar stretches of base calls are locally clustered, and forward and reverse strands are paired creating contiguous sequences. These contiguous sequences are then aligned to a ref-erence in resequencing applications. Each raw read base has an assigned quality score so that the software can apply a weighting factor in calling differences and generating confidence scores to establish the accuracy in sequencing.

6.1.2.3 SOLiD sequencingDeveloped in 2007, Supported Oligo Ligation Detection (SOLiD)

process works on the principle of color-space coding (also known as 2-base encoding) using genomic library construction and step-wise ligation followed by sequencing (Fig. 5.31) (Voelkerding et al., 2009).

The genome to be sequenced is randomly fragmented and adapter sequences are attached to the resulting fragments gener-ating a library. Each adapter-attached molecule is hybridized to agarose beads and clonally amplified through an emulsion PCR


reaction. The beads are covalently anchored to a glass slide and sequenced through multiple rounds of sequencing using progres-sively offset primers and a set of four fluorescent-labeled, dinucle-otide interrogation probes.

Each interrogation probe is an octamer, which consists of (3′-to-5′ direction) 2 probe- specific bases followed by 6 degenerate bases (nnnzzz) with one of 4 fluorescent labels linked to the 5′ end. The 2 probe-specific bases consist of one of the 16 possible 2-base combinations. Complementary oligonucleotides lígate to the template producing a fluorescence signal that is recorded subsequently detecting two bases at a time. Then the oligonucle-otide is cleaved and the next round of ligation continues. After each round of ligation, two new nucleotides are detected and

Figure 5.31. SOLiD Sequencing: (A) Interrogation probes, octamers, consisting of (3′-to-5′ direction) 2 probe-specific bases followed by 6 degenerate bases (nnnzzz) with one of 4 fluorescent labels linked to the 5′ end. (B) Ligation Cycle 1 that incorporates two probe specific nucleotides. (C) After each round of ligation two new nucleotides are detected resulting in fluorescence acquired at every 5th base. (D) Detection of other bases including the adapter bases after four more ligation cycles, using progressively offset primers, (n, n-1, n-2, n-3, and n-4) and determining the template sequence by correlating known adaptor sequence with color-space coding. Adapted from Voelkerding et al. (2009).


corresponding fluorescence measurements are captured at every 5th base.

The entire process is repeated four more times with the use of progressively offset primers, (n, n-1, n-2, n-3, etc.), allowing the detection of other bases including the adapter bases. During Data Analysis, the template sequence is determined using the known adapter sequence in conjunction with the color-space coding. The read length of this technique is 25 to 35; approximately 40 million beads can be sequenced. The sequencing output of this method is 2 to 4 Giga bases. Since each base is probed twice, the accuracy of this method is very high.

6.1.2.4 Ion PGM sequencingIon Torrent sequencing technology can sequence DNA by

directly translating chemical signals into digital information (Fig. 5.32) (Kchouk et al., 2017). The sequencing chemistry uses a semiconductor chip containing microwells wherein each microw-ell behaves as a small pH meter. The Ion PGM sequencing works on the principle that when a nucleotide is incorporated by the polymerase in the DNA molecule, then a proton is released, result-ing in a detectable local change of pH.

Like other NGS techniques, Ion Torrent sequencing requires the DNA to be fragmented and adapters ligated to each frag-ment facilitating its attachment to a bead. The fragments are then amplified using an emulsion PCR. These beads are soared onto

Figure 5.32. Ion PGM Sequencing: (A) Genomic DNA (B) DNA fragmentation and Library construction (C) Clonal Amplification through emulsion PCR (D) Deposition of clonally amplified beads and sequencing enzymes into the micro-well on the semiconductor chip (E) & (F) Sequencing cycle and subsequent detection of pH change upon the release of H+ ions when a base is incorporated. (As adapted from Kim 2012; EBI).


the Ion Torrent semiconductor sequencing chip where each bead is deposited into a single microwell.

Each microwell of the Ion Torrent semiconductor sequencing chip contains about million copies of a DNA molecule. The nucle-otides are fed to the chip in sequential cycles with one nucleo-tide consumed at a time. If a nucleotide is complementary to the sequence of the DNA molecule in a microwell, it will be incor-porated and hydrogen ions are released. The pH of the solution changes in that well and is detected by the ion sensor.

The voltage intensity is recorded directly proportional to the number of identical bases incorporated. For example, if two iden-tical bases are incorporated, the voltage intensity is double, and the chip records two identical bases. Likewise, if a nucleotide that floods the chip is not a match, no voltage change is recorded and no base is called. Because this is direct detection, each nucleotide incorporation is measured in seconds enabling very short run times.

The data generated on the Ion PGM sequencer are automati-cally transferred to the required Torrent Server. The acquired data are then run through signal processing and base calling algo-rithms that assemble the DNA sequences associated with individ-ual reads into a single long consensus. Torrent Server hosts web pages where summarized data results can be viewed and the data themselves can be downloaded using industry standard data for-mats like SFF, FASTQ, or SAM/ BAM. and can be imported into any number of NGS data analysis solutions designed specifically to suit the analysis needs.

6.1.2.5 Pacific biosciences SMRT sequencingSingle-molecule real-time DNA sequencing is based on the

DNA replication process that occurs naturally within a cell every time the cell divides (Kchouk et al., 2017). The PacBio SMRT tech-nology provides longer read lengths in contrast to other NGS methods that provide shorter read lengths (Fig. 5.33).

The technique uses Phospho-linked nucleotides, each labeled with a unique fluorescent dye. For sequencing, a DNA library is prepared by ligating hairpin adapters onto the DNA molecules forming a construct termed as SMRTbell.

A primer and a polymerase are annealed to the adapter and the library is loaded on a SMRT Cell containing nano-scale observa-tion chambers called as “Zero Mode Waveguides or ZMVs.” The SMRTbells are then loaded into the ZMVs where the polymerase within each ZMV incorporates fluorescently labeled nucleotides, emitting a fluorescent signal that is recorded by a detector cam-era in real time. The acquired data can be analyzed using many


PacBio-specific tools and pipelines (including those for demul-tiplexing, creating CCS reads, long amplicon analyses, de novo assemblies, and epigenetic analyses) that are available in PacBio’s SMRT analysis suite via the command line or their SMRT Portal and SMRT Link graphical user interfaces.

6.1.2.6 Oxford nanopore sequencingOxford nanopore sequencing allows the sequencing of

intact DNA strands regardless of their length (Fig. 5.34) (Kchouk et al., 2017). The DNA to be sequenced is attached to an enzyme that unwinds the DNA when the enzyme–DNA complex approaches the nanopore feeding single-stranded DNA such that one base passes the protein pore at a time. Each nucleotide produces a characteristic disruption in the current as it passes through the nanopore, producing events called “Squiggles.” The deflection is recorded and the base is called in real time.

6.2 DNA sequencing: application in foodborne-pathogen identification approaches

The longer read length eliminates the need for specialized tools to be used for sequencing and assembly. The speed and accuracy

Figure 5.33. Pacific biosciences SMRT sequencing: (A) Genomic DNA (B) Library construction by ligating hairpin adapters onto the DNA molecules forming a construct termed as SMRTbell (C), (D) & (E) The SMRTbells are then loaded into the ZMVs where the polymerase within each ZMV incorporates fluorescently labelled nucleotides, emitting a fluorescent signal that is recorded by a detector camera in real time. Adapted from Rhoads et al., 2015, Ardui, Ameur, Vermeesch, and Hestand, 2017 and Sebra et al., 2017.


of nanopore sequencing have enabled its use in a variety of appli-cations including Whole Genome sequencing, species identifica-tion, and metagenomic experiments.

DNA sequence-based pathogen identification has been the method of choice by many researchers due to its high discrimina-tory power, 100% typeability, and good reproducibility. However, DNA sequencing, using the first-generation sequencing methods, requires 2–3 days to complete a test, and has limited availability and costs higher than other typing methods (Newell et al., 2010; Wassenaar & Newell, 2000).

The NGS-based newer methods like Whole Genome Sequencing (WGS) and Metagenomic Analysis have evolved into approaches that can be used to simultaneously detect thousands of uncultur-able microorganisms present in a food sample, that are otherwise difficult or impossible to analyze (Mayo et al., 2014).

6.2.1 Whole genome sequencingWGS provides a specific line of information for one particular

organism, to compare against a lot of different microorganisms, either to rule them out, or to say they are closely related. It is a reli-able, automated, and cost-effective technique that can be performed in a single comprehensive procedure, allowing rapid and sensitive pathogen identification and reporting (Lakicevic, B., et al., 2017).

Short-read technologies (e.g., Illumina and Ion PGM sequenc-ing) are best suited for high-throughput applications due to their high accuracy and low per base sequencing costs. They are the main technologies used for routine WGS by government agencies. Long-read sequencing technologies (e.g., Pacific biosciences SMRT sequencing), however, due to higher cost and lower throughput,

Figure 5.34. Oxford nanopore sequencing: (A) Genomic DNA (B) Enzyme–DNA complex approaches the nanopore and the enzyme unwinds the DNA feeding one base at a time through the nanopore (C) Characteristic current disruptions recorded for each base that passes the nanopore. (D) Resulting events (Squiggles) used to read the corresponding base in real time. Adapted from Bayley, 2015 and Magi, Semeraro, Mingrino, Giusti, & D’Aurizio, 2017


are not the method of choice for routine WGS; however, they can be used in combination with short-read data (USPOULTRY, G.A; https://www.uspoultry.org/foodsafety/docs/WGS_pathogen_characterization_072916-03.pdf).

WGS-based identification methods have been most promising in providing ways to associate a foodborne pathogen’s genomic information with its geographic location and applying the prin-ciples of evolutionary biology to determine the relatedness of the pathogens (Fig. 5.35 and 5.36).

Figure 5.35. Schematic workflow of the NGS approaches that may be followed when implementing Whole Genome Sequencing (WGS) or Whole Metagenomic Sequencing (WMS) methodologies for surveillance in foods. As adapted from Oniciuc et al. (2018); Sekse, Holst-Jensen, and Dobrindt (2017) and Vardaka, Kormas, Katsiapi, Genitsaris, and Moustaka-Gouni (2016).

Figure 5.36. Food illness Outbreak Investigation using NGS. Adapted from FDA.

https://www.uspoultry.org/foodsafety/docs/WGS_pathogen_characterization_072916-03.pdf

https://www.uspoultry.org/foodsafety/docs/WGS_pathogen_characterization_072916-03.pdf


Information about the geographic areas of the pathogens can facilitate tracking down the root source of contamination for a food product, especially in multi-ingredient food prod-ucts whose ingredients come from different states or countries. Faster identification of the source of contamination ensures timely actions that can be taken to remove the harmful ingredient from the food supply, thereby averting more illnesses and deaths (FDA, U.S.; https://www.fda.gov/Food/FoodScienceResearch/WholeGenomeSequencingProgramWGS/ucm422075.htm).

The increase in information, produced through WGS and faster data processing and sharing capabilities provided by NGS platforms, has helped the government agencies and Public Health Laboratories in improving the understanding and tracking of pathogens, enabling better prevention and control measures to be implemented in outbreak situations.

6.2.2 Whole metagenomic sequencing (WMS)Metagenomics is a relatively new molecular technique that is

used to interrogate the presence and the functional potential of all microbial communities (or “Microbiome”) in a biological simple (Figs. 5.35 and 5.36) (Oniciuc et al., 2018).

In contrast to detecting one pathogen at a time in WGS, metagenomics offers a less-biased pathogen detection methodol-ogy aloowing the setection of all microbial DNAs present in the given sample. Public health labs and food regulatory agencies around the globe are adopting metagenomics as a revolutionary new method that will eventually replace existing conventional microbial typing technologies.

The technique allows the detection of extremely low level of microbial species present in the food samples, analyzing the target microbes as well as many other organisms including plant and ani-mal species, at the same time, within the same analysis (Beans, 2017).

By comparing the genomic sequences from the metagenom-ics analysis to the reference database, the relative quantity of each individual microbe in the community can be identified and cal-culated, thereby highlighting the problem pathogens. By focusing on RNA rather than DNA, a better sense of the microbial species that are actively producing proteins and, therefore, still alive can be sought.

6.3 Challenges with NGS methodsData deluge is the biggest challenge associated with NGS-

based methods. To accurately identify a pathogen from among the diversity of microbial agents, researchers need substantially

https://www.fda.gov/Food/FoodScienceResearch/WholeGenomeSequencingProgramWGS/ucm422075.htm



more data. The huge data generated from NGS experiments lead to “Big Data” problem of processing, storing, and sharing the data (Beans, 2017).

The other big challenge to the successful implementation and use of NGS-based methods in public health is the political, legal, and psychological obstacles to enable free data sharing within the scientific community (van Panhuis et al., 2014). This poses a need to integrate the data sharing policies into current regulatory prac-tices with other emerging policies of food regulatory and public health institutions, which will increase the availability of micro-bial sequences across the globe and will provide better regulations to help making decisions around public health risk assessment and control.

To make genomics reach its potential for food safety, these challenges must be addressed, without which the potential of these NGS approaches will be reduced to that of any other typing method.

7 Molecular techniques for GMOs and transgenic food

Genetically modified organisms (GMOs) or transgenic organisms are designed using genetic engineering techniques (recombinant DNA technology). DNA molecules from differ-ent natural sources are combined into one molecule to create a new set of gene, and then this construct is transferred into an organism, modifying its natural genome permanently. For con-ventional techniques that involve plant and animal breeding methodologies for genetic modification, the term GMOs cannot be applied (Holingworth et al., 2003). GM food products were first introduced to the market in the early 1990s. Presently, most GM foods available in the market are transgenic plant products such as soybean, corn, canola, and cotton seed oil, and cultivation of these is generally prevalent in the developed countries that domi-nates global trade in these commodities. Although the animal products have also been developed, as of July 2010, none of them actually reached market (Bob Holmes, 2010). During 2009–10, only USA itself cultivated about 86% of the corn, 93% of the cot-ton soybean and rapeseed (canola) crops compared to only 26% corn, 49 % cotton, 77 % soybean, and 21% rapeseed worldwide (GM FOOD, 2010). Besides this, the International Service for the Acquisition of Agri-biotech Applications (ISAAA) had estimated that about 15.4 million farmers from 29 countries cultivated GM crops over more than 148 Million hectare worth $ 11.2 billion in


2010. It is important to mention here that over 90% or 14.4 mil-lion were small resource poor farmers from developing countries. Developing countries grew 48% of global biotech crops in 2010—they will exceed Industrial Countries before 2015 (ISAAA, 2010).

In contrast, the trend within the European Union (EU) is nega-tive as the initial release of GM crops and cultivation was inhibited by government regulation in the early 1990s. GM foods have either not gained worldwide acceptance or have slow acceptance due to consumer suspicion for public health safety, environmental con-cerns, transparent regulatory oversight, and mistrust in government bureaucracies and controversial debates. Above mentioned factors have raised possible issues, among GM food consumers, as inter-organism gene transfers or introduction of antibiotic resistance genes may lead to possible allergenicity, gastrointestinal diseases, etc. Therefore, with the fast pace of development and commercial-ization for the use of increasing number of transgenic or genetically modified (GM) food during the last two decades, the demand for reliable analytical data is increasing. These issues remain the main driving force behind analytical developments in the area of GM food or feed. And, there is a need to investigate and monitor the presence, identity, and quantity of GM events in complex types of samples like seeds, microorganisms, and processed food.

7.1 Existing regulatory laws for GM foods available in market

Two decades have passed ever since the GMOs have been intro-duced in the market; no strict regulatory laws exist in most of the countries except some European countries. GM samples vary from raw commodities to highly processed foods and testing require-ments extend from a general GM screen to a method capable of identifying and quantifying a particular GM crop. Labelling legis-lation and trade requirements vary from one country to another, leading to the rapid development of numerous tests to detect GM component. US legislation follows “principle of substantial equiv-alence” and has recommended voluntary labeling of bioengi-neered foods and asked companies to notify the US Food and Drug Administration (FDA) of their intent to market GM foods at least 120 days before launch. The term “Substantial equivalence” means that a GM product is not distinct in essence from a conventional one, and thus its release can be considered under existing legis-lation like the Plant Protection Act (PPA), the Federal Food, Drug and Cosmetic Act (FFDCA), the Federal Insecticide, Fungicide and Rodenticide Act (FIFRA), and the Toxic Substances Control Act (TSCA) (Marmiroli et al., 2008). The responsibility for various


aspects of GM risk assessment is delegated to Food and Drug Administration (FDA), Department of Agriculture (USDA), Animal and Plant Health Inspection Service (APHIS), and Environmental Protection Agency (EPA), whereas EU system takes “process-based” approach for GM food/feed and has implemented amal-gam of regulations, directives, and amendments through various decisions of European Commission (EC), European Parliament (EP), relevant Council of Ministers, and each Member States. The presence of GM material in food, feed, and food products is governed by 1829/2003, which insists on an essential labelling for all products containing GM-based materials above 0.9% (EC Regulation, 2003). The term “genetically modified” must appear in the list of ingredients immediately following the relevant ingre-dient. For nonauthorized GM ingredients, the threshold is set at 0.5%, provided that the source GMO has been pre-evaluated, and that an appropriate detection method for its presence is available. For seed, the threshold is 0%, that is, all GM seeds must be labeled according to 2001/18/EC. Till today, in the European Union (EU), the company applying for authorization of GMOs as food and feed must prove its safety for human and animal health and provide proper GM event-specific detection and quantification method. European Union Reference Laboratory for GM Food and Feed (EURL-GMFF) validates the protocols/methods for GM food iden-tification with reference to EC regulation No 1829/2003 (Regulation (EC) No 1829/2003. Implementation of the requirements of the ISO 17025 standard, EC regulation 882/2004 and 619/2011 (PN-EN ISO/IEC 17025:2005, Regulation (EC) No 882/2004 and 619/2011) is constantly thriving researchers to drift toward improved methods for GMO detection. qPCR to digital PCR and droplet digital PCR (ddPCR) is an example of such development. NGS to newer gen-erations of sequencers implementing whole genome sequencing (WGS) and Whole Metagenomic Sequencing (WMS) offer another level of accuracy, precision, and speed with millions of unlinked genomes being identified in single go.

If the GM components of a food or feed are considered by some legislation as contaminants, there will be considerable demand for reliable analytical methods capable of detecting, identifying, and quantifying either the presence of GM DNA or GM protein, at the farm gate, the processor, and the retailer level. Basically, two different types of analysis can be targeted for this purpose, that is. GM product formation or the parts of the transgenic DNA, which were inserted by biotechnological techniques into the genome of a natural plant, or the protein expressed by this transgenic DNA. Detection of expressed protein, however, is beyond the scope of this chapter. This section provides different kinds of molecular


detection techniques available of GM food and feed for academi-cians and researchers. Table 5.2 gives some important definitions that help understanding GM detection methods:

7.2 Reference materials, laboratory testing, and method validation for detection of GMOs

GMOs prior to being tested must be provided with suitable spe-cific reference materials to validate analytical procedures and for assessing the performance of methods and laboratories. Reference material should be focused on raw material or base ingredients rather than on finished foods. Generally, for grains altered DNA or expressed proteins have been used as reference material that real-istically mimics real-life test material (type of sample matrix and consistency compared to test grain samples). In some cases, both

Table 5.2 Some important definitions used for GMOs or transgenic organisms.

Construct An engineered chimeric DNA sequence designed to be transferred into a cell or tissue. Typically, the construct comprises the gene or genes of interest, a marker gene, and appropriate control sequences as a single package.

Event Transformation of an organism by inserting a piece of DNA (the Construct) into the genome. Events vary in the particular location that construct is inserted into host genome and may vary in precise DNA sequence inserted into the organism.

Trait Genetic traits are those aspects of an organism that are controlled by genes, for example, resistance to the herbicide glyphosate in Roundup Ready soy.

Construct-Specific DNA tests that are designed to detect sequences that have been inserted into the genome by genetic engineering. Examples include the junctions between the different components of the construct (e.g., promoter).

Event-Specific DNA tests that are designed to detect the junction sequence between the inserted construct and the genomic DNA. These tests are suitable for Relative Quantification and for identification of a specific GM event.

Quantitative (absolute)

Tests that measure the amount of a substance, e.g., how many milligrams of a specific protein or how many copy numbers of a specific DNA sequence are present. Results are presented as an absolute value. The larger the size of the sample being tested, the higher the absolute quantity.

Quantitative (relative) Tests that measure the amount of a substance relative to another substance, e.g., how many copy numbers of a specific DNA sequence are present per genome. Results are presented as a percentage. This percentage does not change with an increase in the size of the sample being tested. The relative quantification is required for compliance to the GMO labeling legislation.


genomic and plasmid DNA have been used as reference material; the former being more realistic in terms of matrix effect, whereas the latter is easier to prepare in large quantities and might pro-vide greater consistency. DNA-based methods are better served through combinations of several positive controls. Methods like rt-PCR-based analytical measurements need matrix materials to control and calibrate the measurement step with appropriate solutions large number of reference materials can be taken from The Institute of Reference Materials and Measurements at the Joint Research Center in Geel, Belgium (Trapmann & Emons, 2005).

The general requirements and definitions for GMO detec-tion have been specified by International Organization for Standardization (ISO) document 24276:2006. It focuses mainly on PCR-based methods where detailed guidelines for achieving vali-dation have been documented. Community Reference Laboratory for GM food and feed (CRL-GMFF), at the Joint Research Centre of the European Commission, Biotechnology & GMO Unit, estab-lished by regulation 1829/2003 oversee the process of validation in Europe. The protocols for GMO detection can be submitted at URL http://gmo-crl.jrc.it/statusofdoss.html The status and list of such submitted/available protocols or validated methods (about 25) targeted to specific events in maize, rice, sugar beet, and cot-ton can be referred through this (Marmiroli et al., 2008). Dong et al. (2008), 2015 have established and published a web-based database containing details (experiment protocol, primer sequence, etc.) for all available detection methods for DNA/protein analysis, irre-spective of their validation status. Certified Reference Materials (CRMs) are used for calibration or quality control of GMO quanti-fication measurements, typically carried out by quantitative real-time polymerase chain reaction (qPCR) for different GM events in maize, soybean, potato, sugar beet, and cotton including new plant species for testing and control laboratories world-wide. The available concentrations differ for individual GMO event (and the set of CRM) and range from nominal 0 g/kg to 1000 g/kg.

7.3 Categories of molecular detection techniques for GMOs or transgenic food

Production of a GM food involves either integration or unique transformation event (deletion or substitution of a part of an organism’s genome) of a novel DNA sequence into the genomic DNA. GM products hold one or more inserted gene(s) that nor-mally exhibit some additional characters than natural plant char-acteristics. A typical gene construct is composed of a promoter functioning as a start signal, a gene of interest, and a terminator

http://gmo-crl.jrc.it/statusofdoss.html


functioning as a stop signal for regulation of gene expression. Raw material (e.g., grains/seeds) and processed products (e.g., foods, oils) resulting from GM crops might thus be recognized by testing for the presence of introduced DNA. Fig. 5.37 shows four categories for detection of GMOs using molecular techniques (Holst-Jensen, Rønning, Løvseth, & Berdal, 2003) related to level of specificity corresponding to the composition of the inserted/substituted DNA fragment.

7.3.1 Category I: “Screening Target” specificThe bulk of GM plants are transformed with “constructs” that

generally contain “Cauliflower Mosaic Virus (CaMV) 35S pro-moter (P-35S)” and/or the CaMV 35S terminator (T-35S) or the “Agrobacterium tumefaciens nopaline synthase terminator” (T-Nos) and antibiotics resistance (like ampicillin (bla) antibiotics, neomycin/kanamycin (nptII) antibiotics, etc.) via common clon-ing vectors (pBR322 or pUC19). Therefore, PCR methods of cat-egory 1 target such regions for screening of genetically modified materials. These screening target specific methods cannot be used to identify the GMO since the presence of one of the screening tar-gets does not necessarily indicate the presence of GMO-derived DNA. The source of P-35S or T-35S could be naturally occurring CaMV, and also Agrobacterium or other soil bacteria containing one or more of the targets are present in soil. An added source of uncertainty may be presence of cloning vector DNA in the DNA polymerase, for example Ampli-Taq (Applied Biosystems) con-tains amplifiable bla DNA (Holst-Jensen et al., 2003).

7.3.2 Category II: “Gene” specificAs shown in Fig. 5.22, “gene-specific” targeting offers more

specificity and better availability of choice. Normally, a positive

Figure 5.37. A typical “transgene construct” (host genome with transgene promoter, gene, and terminator) and four categories of detection methods: screening target specific (generic transgene sequences), gene specific, construct specific, and event specific (Marmiroli et al., 2008).


signal with this method implies that GM-derived DNA is present, and in many cases, it will even be possible to identify from which GMO the DNA is derived.

7.3.3 Category III: “Construct” specificThis category targets the junctions between adjacent elements

of the gene construct, for example, between the promoter and the gene of interest to get a positive signal only in the presence of GM-derived material. Though, the full gene construct may have been transformed into more than one GMO, or may be used in future transformations, for example, pV-ZMBK07 and pVZMGT10 into the following GM maize: Mon809 (1 copy of both), Mon810 (1 copy of the former), Mon832 (1 copy of the later), and Mon80100 (unknown number of copies, possibly other related plasmids) (GMO database, 2002).

7.3.4 Category IV: “Event” specificThe only unique signature of a transformation event is the

junction at the integration locus between the recipient genome and the inserted DNA. This junction is the target of category IV (event-specific) methods.

“Screening targets” methods have the broadest area of appli-cation, as they are able to identify multiple GMO traits. The “trait-specific” methods detect a specific novel protein while “con-struct-specific” methods detect a specific DNA construct used to introduce the novel trait. “Event-specific” methods are used for detection of a transformation event and have been considered most appropriate among all four categories. Protein detection methods, however, rely on the amount of protein produced or “expressed” by the novel DNA construct and also on whether that protein is expressed in the part of the plant being tested. Protein detection methods are generally less sensitive than DNA detec-tion. DNA detection methods are versatile and very sensitive, although cautious sample preparation is needed to extract DNA to avoid assay inhibitors that are naturally present in raw/processed food and feed (Emons, 2010).

There are various molecular techniques that have been tailored to fulfill the specific needs for molecular analysis/experiments for detection of food pathogens as discussed in sections 3, 4, 5 and 6. However, GMOs have been reported to be detected generally using various PCR-based techniques for qualitative, quantitative, and simultaneous analysis. GMOs can also be detected by immu-nological methods, for detection of the cognate proteins (limited to tissues in which the transgene is expressed) (Garcıa-Canas,


Gonzalez, & Cifuentes, 2004) and using biosensors utilizing vari-ous combinations of nanomolecular materials and biomarkers/bioreceptors (Kumar & Arora, 2020). Since DNA is more stable than protein, molecular techniques (like PCR) are usually preferred for better reliability and sensitivity. Following are some of the molecu-lar techniques that have been utilized for the detection of GMOs.

7.4 Southern blottingSouthern blotting involves the isolation of DNA from selected

animals, digestion of DNA with restriction enzymes, electropho-resis on agarose gels to separate DNA by size, denaturation of the DNA, and transfer of the DNA to a membrane. This membrane (either nitrocellulose or more recently nylon) is then hybridized with a specific probe (complementary to the transgenic sequence of interest). The probe is (usually radioactively, calorimetrically, or chemiluminescently labeled) hybridized to the transgene DNA to visualize the position of the transgene transferred onto the membrane.

Southern blot analysis can be used to: (1) Demonstrate the presence or absence of a transgene in the sample; (2) Determine whether chromosomal integration has occurred; (3) Identify the position of integration relative to other samples; (4) Determine whether homologous recombination (directed integration) occurred; (5) Determine copy number of transgene; and (6) Analyzing the stability of the transgene with regard to reintegra-tion and/or and replication over time and through future genera-tions, that is the frequency of mutation/rearrangement within or adjacent to the transgene. This is no longer the method of choice for detection of transgenic DNA or transgene copy number since the PCR-driven methods have been developed. However, southern blotting analysis is still the best method for identifying positions of integration within the genome, and for analysis of the stability of integration over multiple generations.

7.5 PCRAs described in section 3 PCR is one of the most popular and

accepted methods by the regulatory authorities for detection of transgenic foods and feed via use of primers specific to the ‘trans-gene sequence(s)’ through its various formats such as qualitative PCR, end-point quantitative PCR, and quantitative real-time PCR, and exhaustive limiting dilution PCR (Ahmed, 2002). Since it has become an essential analytical tool for researchers working in the foodborne pathogens field and is reported in more than 300,000 scientific publications for different areas of food science research,


including food safety, due to its versatility, specificity, and sensi-tivity. Generally, PCR assays require a minimum number of target DNA sequences to be present in the template, and the sequence of the target DNA is known. The extraction and purification of DNA from the sample, however, is a critical step. PCR technology is one of the most trustworthy methods to detect the presence of little and/or poor quality DNA sequence from range of samples (like heavily aged or highly processed ones). An interesting book based on PCR-based methods for bacterial pathogens in various matrices include food, and clinical samples describes in detail the factors, sample processing, and protocols (Sachse and Frey, 2003). This method also cites an example Shigella (shiga producing E. coli) was detected using pre-enriched sample using PCR in food sample.

7.5.1 Competitive PCRAs the name itself suggests, this type of PCR is used to estimate

the amount of initial template after PCR amplification in competi-tion to other similar templates. Two different templates are used for amplification of two different genes. Two target sequences with very similar features are co-amplified in a single reaction tube. These two targets compete for available nucleotides, prim-ers, and DNA polymerases; the relative quantity of end product is assumed to correspond to the relative quantity at the beginning of the first PCR cycle. Quantitation is done by comparison of the amount of end product (endpoint quantitation), that is when the PCR reaction is completed. Since this competitive PCR requires development of suitable competitor molecules, it is highly sensi-tive to the starting concentrations and dilution of template DNAs (Holst-Jensen et al., 2003).

Fig. 5.38 shows one of the examples of double competitive PCR that for each of the two targets (GMO and plant), a series of

Figure 5.38. Double competitive PCR for GMO target (G1 to G6 wells) and reference plant species target (P1 to P6 wells) in agarose gel along with a molecular size marker (M) on either side and between the series (Holst-Jensen et al., 2003).


dilutions (e.g., fourfold) are made and to each dilution a competi-tor target molecule is added in such a way that same quantity of competitor is added. The competitor should be as similar to the target, and at the same time amplified product should be easily distinguishable from target. During process of PCR amplification, competitor and target will compete for reagents and the initial copy number ratio will be approximately maintained at the end point of the reaction. For the dilution of target when the copy numbers of competitor and target are the same, both will yield the same quantity of amplification product and the visible bands in the gel will be of equal intensity (i.e. equilibrium). Boxes shown in Fig. 5.23 indicate the two points of equilibrium (GE and PE) for the each series where equilibrium concentration can be calculated as shown in Eqs. (5.5)–(5.7).

GEG G3 4

2= +

(5.5)

PE P3= (5.6)

GM contentGEPE

Therefore, 100= × (5.7)

This competitive PCR compensates for the fluctuations of amplification efficiency using co-amplification of each target sequence with same set of primers and provides absolute quan-tification. This, however, suffers from low throughput, due to multiple PCRs required for the titration of each sample and gel electrophoresis. An improved version of competitive PCR has been developed in a microtiter well-based assay format using 35S promoter sequence and plant-specific reference gene as internal standards of constant amount (e.g., 1000 copies). The four ampli-fied fragments were hybridized with specific probes and captured on a solid phase to detect the hybrids via luminescence detection (Marvropoulou, Koraki, Ioannou, & Christopoulos, 2005). Also, multiplex quantitative competitive PCR was developed to detect multianalyte hybridization using specially encoded microspheres (Kalogianni, Elenis, Christopoulos, & Ioannou, 2007).

7.5.2 Quantitative or real-time PCRReal-time PCR as explained in Section 3.5 is used to moni-

tor the real-time progression of the PCR amplification process through detection chemistries like TaqMan probe, SYBR green, and Molecular beacon. Quantitative real-time PCR (qRT-PCR) is also one of the powerful means of quantifying GM material in

GE=G3+G42

PE=P3

There-fore, GM content=GEPE×100


agricultural and food products through the fluorescent signal. For GM detection, two parallel reactions (reference material and GM material), each containing the same amount of template DNA, are commonly performed (Karlen et al., 2007).

Quantification can be achieved by: A comparison based on the cycle threshold (C

t) of the two amplified sequences (the ∆C

t method)

or titration against standard curve (Bustin, 2000; Gibson, Heid, & Williams, 1996; Higuchi et al., 1993). PCR, when used in exponential phase (when reagents are not limiting), can be used to quantitate the target DNA by measuring the change in fluorescence propor-tional to the accumulation of PCR product. As shown in Fig. 5.30 by plotting fluorescence against cycle number (so an exponentially increasing quantity will give a straight line), a threshold for detec-tion of fluorescence above background is determined. The point at which the amplification curve crosses the threshold is the cycle threshold (C

t) of the sample. The C

t values from a dilution series of

known DNA quantity are used to generate a standard curve, which is used to quantify samples with unknown amounts of DNA.

Under normal circumstances, the amount of PCR product dou-bles each cycle as shown in Fig. 5.5 and can be calculated using Eq. (5.1). If there is a doubling at each cycle, the reaction is said to be working at 100% efficiency. qRT-PCR amplifications should operate as close to 100% efficiency as possible. Efficiency is related to the slope of a standard curve plotted as C

t versus log concentra-

tion. Eq. (5.8) for determining efficiency is:

= −

×

−

Efficiency 10 1 100%slope

1

(5.8)

Fluorescence signal corresponding to increased amount of amplification product can be measured and visualized on a com-puter screen. Software can immediately convert the signal into quantitative estimates within 30 min compared to 3 h or more as in case of competitive PCR. As mentioned earlier, quantitation can be done either by direct comparison of the C

t-values of the two

(∆Ct method) or by comparison with a standard curve. The advan-

tage of standard curve quantitation is that Ct-values are compared

only with Ct-values of the same amplicon. So, with standard curve,

the final quantitative estimate is based on comparing estimated quantity of GM to estimated quantity of reference. The estimate is therefore the ratio of quantity to quantity, not of PCR cycle to PCR cycle. Since, real-time PCR requires very expensive labora-tory equipment, and therefore cheaper alternatives giving similar accuracy and comparable throughput are welcomed.

Fig. 5.39 shows a typical quantitative real-time PCR to estimate the amount of % GM. Each amplification is represented by separate

GE=10-1slope-1×100%


curve and quantitation of reference “R” and GM material “M” is done in comparison to the standard curve or regression line when a curve is plotted as number of cycles versus fluorescence signal. Lesser the initial number of cells, higher is the cycles required to achieve the threshold. For an unknown sample, two reactions, one targeting a reference (R), and one targeting a GM-specific (G) sequence, are performed and difference in C

t (∆C

t) for the two tar-

gets (∆Ct = C

tG–C

tR) is calculated to estimate the GM content using

the formula mentioned in Eq. 5.9:-

∆× =

CGM

1

2100% %

t (5.9)

However, the use of ∆Ct for quantitation is only valid if the two

targets are amplified with the same efficiency. The GM content can also be estimated by comparison of the initial target copy numbers of the two targets, using the formula GM % = N

G/N

R × 100% with

reference to standard curve or regression line where NG and N

R are

the initial number template for GM and reference template. Guo et al. (2009) reported one papaya-specific gene, Chymopapain (CHY), as one suitable endogenous reference gene, used for GM papaya identification. In the CHY conventional PCR assay and real-time quantitative PCR assay, the limit of detection (LOD) was 25 and limit of quantification (LOQ) was 12.5 copies of haploid papaya genome, respectively.

A qRT-PCR reaction may be uniplex, duplex, or multiplex in terms of number of samples to be analyzed and in terms

12∆Ct×100%=%GM

Figure 5.39. Quantitative Real-time PCR for estimation of GM (Holst-Jensen et al., 2003).


differential fluorescence labeling. In this case, differential fluo-rochrome labels (with overlapping emission spectra e.g., SYBR Green I and LC green) are utilized by exploiting different ampli-con melting curves in a “sequence-specific” method. Some of the examples are as follows:1. Uniplex assays using primers and TaqMan probe.2. Duplex assays with reference gene and relevant certified ref-

erence materials (CRMs) for semiquantitative estimate of GM sample for P35S or T-Nos. Both event-specific and species-spe-cific qRT-PCR assays based on TaqMan or similar chemistries have been duplexed by labeling each probe with different fluo-rochromes (Marmiroli et al., 2008).

3. SYBR Green-based triplex assay has allowed the simultaneous detection of Maximizer 176, Bt11, and MON810 in GM maize, and has recently been demonstrated to be effective in both seed and meal samples with a limit of detection of 1% (Hernán-dez, Rodríguez-Lázaro, Esteve, Prat, & Pla, 2003).

4. The fluorophore double-stranded probe’s multiplex quantita-tive PCR (FDSP- MQPCR) method has been recently described for the simultaneous detection of P-35S and T-Nos. In a test of ten soybean flour samples, FDSP-MQPCR gave quantitative re-sults within 5 h, with accuracy estimated to be at least 97.0% or higher over a range including from 0.5% to 5.0% GMO in stan-dard materials (Codex Alimentarius Commission, 2004; Waib-linger, Ernst, Anderson, & Pietsch, 2008)

A wide variety of commercial qPCR kits are available for detection of single microorganisms from different companies as iQ-Check from Bio-Rad, DuPont QualiconTM BAX, foodproof Salmonella from Merck-Millipore, AnDiaTec from Roche or MicroSEQ from Applied Biosystems (Chapela, Garrido-Maestu, & Cabado, 2015). The potential presence of GMO is assessed via a screening approach targeting the most common transgenic elements found in GMO, such as p35S (35S promoter from cauliflower mosaic virus) and tNOS (nopaline synthase terminator from Agrobacterium tume-faciens). In addition, some markers more discriminative, such as Cry3Bb, gat-tpinII, and t35S pCAMBIA, and taxon-specific mark-ers could also be used. This step allows establishing a list of the potential GMO present in the tested samples and preventing fur-ther unnecessary assays in the subsequent steps (Angers-Loustau, Petrillo, & Bonfini, 2014; Broeders, Papazova, Van den Bulcke, & Roosens, 2012a,b; Broeders, Fraiture, & Vandermassen, 2015; Barbau-Piednoir, Lievens, & Mbongolo-Mbella, 2010; Fraiture et al., 2014). Quantitative real-time PCR (qRT-PCR) represents the most powerful current means of quantifying GM material in agri-cultural and food products. It operates by continuously monitoring


the amplification reaction, using the strength of the fluorescence signal to indicate the quantity of amplicon present. The specific-ity of qRT-PCR depends on both the chemistry used to monitor amplification and the instrumentation used to monitor the signal.

7.5.3 Multiplex PCRMultiplex or mPCR utilizes several primer pairs to permit the

simultaneous detection of construct-specific multiple target sequences. Typically, for GMO detection, it is simple and cost-effective, where generated products are distinguished from one another on the basis of their differential migration through aga-rose gels. In a nonaplex (nine construct-specific primer pairs) PCR assay, eight GM maize varieties were successfully distinguished from one another in a sample containing 0.25% of each event (Onishi et al., 2005) using both agarose gel and capillary electro-phoresis for amplicon size varying from 110 to 444 bp. The simul-taneous detection of the transgenic events Bt11, GA21, MON810, and NK603 in maize has been achieved by exploiting transgene/plant genome flanking regions, with an LOD of 0.1% for each event using different fluorochrome labels (Nadal, Coll, La Paz, Esteve, & Pla, 2006). A particular advantage of this platform is that it can be readily adapted to a high throughput mode. This mPCR option saves considerable time and effort, and decreases the number of reactions that need to be performed to detect the desired tar-gets in the sample. However, chances of increased formation of misprimed PCR products, known as “primer dimers,” and the amplification of unspecific DNA fragments. Still the advantages with respect to standard methods are the shorter time required. Typical culture methods as per ISO or FDA Bacteriological Analytical Manual—for Shigella spp., E. coli O157, and different human pathogenic Vibrio spp. (V. cholerae, V. parahemolyticus, and V. vulni cus) detection—need two days to guarantee a nega-tive result. Several multiplex qPCR TaqMan strategies have thus been investigated, including mainly the screening markers p35S and tNOS. The throughput of multiplexing with qPCR strategy is relatively limited by the availability of dyes with an emission and absorption spectrum of fluorescence sufficiently distinct to avoid overlaps of signals. This has been demonstrated for maximum six markers till date (GMO, JCR GMO METHODS, http://gmo-crl.jrc.ec.europa.eu/gmomethods/., Bahrdt, Krech, Wurz, & Wulff, 2010)

7.5.4 New PCR-based methods for GMODigital PCR and droplet digital PCR: Two validated qPCR

methods dPCR (as explained in Section 3.6) and droplet dPCR (ddPCR) for quantification of GM maize DAS1507 and NK603 were

http://gmo-crl.jrc.ec.europa.eu/gmomethods/



approved by European Network of GMO Laboratories (ENGL) on analytical method verification (ENGL working group on “Method Verification”). It was reported that these dPCR methods per-formed equally or better than the qPCR methods and optimized ddPCR methods confirmed their suitability for GMO determi-nation in food and feed (Grelewska-Nowotko, Żurawska-Zajfert, Żmijewska, & Sowa, 2018). Droplet dPCR basically is division of sample into more than 20,000 droplets (generated with the help of special oil emulsion) and parallel PCR amplification to achieve very high degree of accuracy and precision. The chamber dPCR (cdPCR), partitioning the sample in several thousands of micro-fluidic chambers, was used to target GM maize MON810 event using a duplex PCR composed of the MON810 event-specific and maize taxon-specific methods. The detection limits of this approach were also investigated (Bhat, Herrmann, Armishaw, Corbisier, & Emslie, 2009; Burns, Burrell, & Foy, 2010; Corbisier, Bhat, Partis, Xie, & Emslie, 2010). Using this method, a wide range of GMO by applying individually twenty-eight element-specific, thirty-six event-specific, and five taxon-specific methods were also developed. Then duplex assays, including one GMO-specific marker with one soybean, maize, or rice taxon-specific marker, were performed by using the ddPCR system to quantify twelve GM soybean, sixteen GM maize, and two GM rice events (Köppel, Bucher, Frei, & Waiblinger, 2015, Köppel & Bucher, 2015). As per dPCR given that maximum two different targets could be identi-fied in one well, the low-throughput power of the dPCR technol-ogy highlights its applicability more suitable at the identification/quantification level than at the screening step.

PCR Capillary Gel Electrophoresis Technology: PCR multiplex CGE makes use of fluorescently labeled primers that allow dis-criminating different amplicons of the same size, and has been also suggested to be applied in the GMO detection field (Vega & Marina, 2014). It has higher resolution compared to PCR but is lower than qPCR and therefore has limited application. Using the PCR CGE system, eight GM maize were identified via a nona-plex PCR including event-specific, construct-specific, and taxon-specific methods (Heide, Drømtorp, Rudi, Heir, & Holck, 2008a; Heide, Heir, & Holck, 2008b). After multiplexing, four GM maize, five GM cotton, twenty-four targets from fourteen GM event, Bt11 maize and GTS40-3-2 soybean events have been detected.

LAMP: As explained in Section 4.1, several LAMP markers have been developed for this approach to detect transgenic elements (Di, Shi, & Shen, 2014). This is a very important method as it does not require any complicated device and also that has ability to tol-erate various inhibitors of PCR reaction.


DNA walking: This is also one of the PCR-based methods, which works similar to genome walking where this molecular technique allows identifying unknown nucleotide sequences adjacent to already known DNA regions in any given genome using specific primers to the known sequence combined to primers dictated by the DNA walking method used. By this way, several sequences of transgene flanking regions and unnatural associations from vari-ous transgenic foods. In order to especially identify unauthorized GMO in European Union, a DNA walking approach using primers specific to the element t35S from the pCAMBIA vector, found in approximately 30% of transgenic plants, was developed (Fraiture et al., 2014; Fraiture, Herman, & Taverniers, 2015). However, the DNA walking strategy is not suitable to GMO containing only unknown elements.

7.6 Array-based methodsArray-based methods are known to screen many targets paral-

lel within same sample and therefore can overcome the difficulties of existing PCR-based techniques when various PCR amplified products are needed to be distinguished on the basis of amplicon length using conventional electrophoresis. The microarray has the potential to combine detection, identification, and quantification of effectively an unlimited number of GM events in a single exper-iment (Aarts, van Rie, & Kok, 2002). Since the microarray provides a systematic way to analyze DNA/RNA variation, it has become a ubiquitous tool in both molecular biology research and clinical diagnostics. Therefore, substantial investments are being made to bring improvements in this technology (Lander, 1999).

Microarrays can be very well employed for the detection of GM, using known transgene sequences where pattern of hybridization (both qualitative and quantitative) will reveal both the GM vari-ety and GM events. However, considering the limitations of this type of conventional solid phase array (like immediate environ-ment effect, amount of target DNA in the sample, stearic effect), use of positively charged matrix (e.g., Nanogen system) gel-based chips (to provide 3D environment to decrease stearic hindrance); microspheres attached with probes held in a liquid suspension (e.g., suspension array technology, Nolan & Sklar, 2002; bead array counter (Edelstein et al., 2000), and customized PCR-independent microarray using 35 S region-specific probes (tiled through avail-able database at GenBank) for direct detection complementary targets from genomic DNA (Tengs et al., 2007) is nowadays intro-duced. Microarray technology combined with multiplex PCR has also been used to estimate the content of various transgenic


maize events, corn invertase, and soy lectin genes (Rudi, Rud, & Holck, 2003). A commercial kit, DualChip GMO, has been devel-oped by Eppendorf Array Technologies (EAT, Namur, Belgium) by coupling multiplex PCR assays to microarray hybridization to capture sequences present in Bt-176 Maize, Mon 810 Maize, Bt- 11 Sweet Maize, Mon 531 cotton, GA21 Maize, and Roundup Ready TM Soya GMO events (Marmiroli et al., 2008). DNA microarrays have slowly evolved for GMO testing due to higher cost input. Combinations of multiplex PCR detection and microarray detec-tion have been developed to qualitatively assess the presence of GMOs. Commercially available DualChip GMO (Eppendorf, Germany; http://www.eppendorf-biochip.com) GMO screen-ing system is successfully validated in a multicenter study (von Götz, 2010). With the use of innovative amplification techniques, promising steps have recently been taken to make GMO detection with microarrays quantitative.

The ligation detection reaction (LDR) has been coupled with an universal array technology to identify and quantify the cryIA(b) gene from Bt176 maize, simultaneously detect five transgenic events and two endogenous controls (soy lectin and maize zein) in food samples, following two multiplex amplification reactions (Bordoni, Germini, Mezzelani, Marchelli, & De Bellis, 2005; Peano et al., 2005). Peptide nucleic acids (a synthetic nucleic acid known to mimic DNA) have been used in the form of arrays to detect DNA mutations (Song, Park, Jung, & Park, 2005), parallel detection of five transgenes and two plant species in both raw material and processed food (Germini et al., 2005).

7.7 Toxicological analysisIntroduction of transgene into a desired food or feed may add

to toxicity in the GMO either by itself or via unintended/unwanted gene expression/consequences of under- or overexpression of genes (Ewen & Pusztai, 1999). Recent investigators conclude that it is necessary to have further investigations for following potentially relevant concerns of GMO consumption: (1) Chronic gastro-intestinal diseases; (2) Possible unexpected viral infec-tion or DNA recombination event in consumers. As discussed in Section 7.1, there are different guidelines/regulations for intro-duction of GMO’s in market by US and European countries. The concept for safety evaluation of food and feed derived from GM crops has been elaborated in the Organisation for Economic Cooperation and Development (OECD) and crystallized in the “Principle of Substantial Equivalence” (OECD, 1993). As per WHO, each GMO food and feed must be assessed on its individual case

http://www.eppendorf-biochip.com


basis. As proposed by Kok and Kuiper (2003), “the principle of substantial equivalence” can be rephrased as the “Comparative Safety Assessment (CSA)” involving comparative assessment of both nutritional and toxicological contents in GM food. Generally, GMOs can be assessed for toxicity; allergenicity; introduced specific component for added feature of toxicity; stability of the construct; nutritional alterations with respect to genetic modifica-tions; and unintended modifications, for example, antibiotic resis-tance. Keeping all these factors in view, until now there is lack of sufficient information about the safety assessment of introduced GMOs in market (Domingo, 2007). Also, there is very less infor-mation available for toxicological studies too, as these may cause unknown adverse effects in consumers. Until now, there are only few short-term studies for toxicity assessment of GMOs. The avail-able studies present only few cases that report to have alterations/adverse effects (e.g., (1) structural changes in ileum and potential hyperplastic development of the ileum (Fares & El-Sayed, 1998); (2) Proliferation of the gastric mucosa (Ewen & Pusztai, 1999); (3) Increase in monocyte, neutrophil activity against bacteria (Winnicka et al., 2001); and (4) alterations in hematological param-eters (Zhuo et al., 2004)] in mice/rats on the consumption of GM potato or rice, respectively. It is, therefore, emphasized to have “long-term” toxicological studies for consumption of GMO food and feed for human and animals (Patel, Torres, & Rosset, 2005).

Greater level of complexity is involved in toxicological analy-sis of GM food compared to natural food and is a topic of serious debate. Researchers who support principle of substantial equiva-lence state that transgenic food in the form of dietary DNA has no effect on direct toxicity itself (Holingworth et al., 2003). This is based on the fact that humans typically consume about 0.1–1 g of DNA in their diet each day (Doerfler, 2000) and some exogenous nucleotides have shown to play important beneficial roles in gut function and immune system (Carver, 1999). Besides this, there are reports about human allergies to naturally existing fruits (e.g., Kiwi) too (Holingworth et al., 2003). Therefore, as mentioned ear-lier, each transgene product must be considered on individual case basis and toxicity testing of the whole crop or derived plant products is essentially required where the composition of the whole crop has been changed significantly compared with the traditional counterpart. For GMO intentionally made to synthe-size secondary metabolites (e.g., insect or pathogen resistance or production of compound of pharmaceutical importance), there is possibility to produce unanticipated secondary compound with unknown toxic properties. It therefore becomes essential to have the metabolite profiling of each GMO with its parent form.


Molecular techniques cannot individually help in studying each of this aspect. Post market surveillance followed by use of new approaches for combined use of techniques like Nuclear Magnetic Resonance, Mass Spectroscopy, spectroscopic analysis, protein profiling, and Energy dispersive X-ray fluorescence spectroscopy would prove to be very useful in this regard.

7.8 Next-generation sequencingNGS has allowed a massive parallel DNA sequencing, and

has provided a powerful tool for high throughput of sequenc-ing for many different samples simultaneously and discriminate them using a wide range of barcodes (Reuter et al., 2016). Two main strategies, sequencing samples that are earlier enriched with sequences of interest (targeted sequencing approach) or whole genome sequencing (WGS) approach). Target sequencing approach utilizes primers targeting maize endogen gene, Bt11 gene, Bt176 gene, soybean endogen gene, 35S/CTP4 construct, CP4-EPSPS element, p35S promoter, and tNOS terminator, from samples containing a low amount of GM targets. Roche 454, DNA walking method (SiteFinding PCR), Illumina technology have been reported for GMO detection. This approach does the analy-sis of pre-enriched DNA fragments of interest proving the pres-ence of GMO in characterizing sequences entirely or partially known beforehand, whereas whole genome sequencing-based approach allows in principle characterizing a sample without any prior knowledge. However, given its relativly high cost which is expected to decrease over the time, prerequisite bioinformat-ics expertise, the targeted NGS strategy could not reasonably be currently applied routinely to all food/feed matrices by the enforcement laboratories. This is additionally burdened by the requirement of adequate computer infrastructures and qualified analysts in bioinformatics for dealing with the generated data in case of WGS strategy (Buermans & den Dunnen, 2014; Liang, van Dijk, & Scholtens, 2014; Willems, Fraiture, & Deforce, 2016).

8 Future prospectsAdvances in molecular techniques have gained an edge among

the existing detection methods of food-borne pathogens due to improved specificity, sensitivity, ease of operation, and faster detection. Traditional culture methods following enrichment can take days to yield results, while molecular techniques and their advanced versions can generate results within few hours. Culture-independent techniques are mostly based on the analysis of


microbial nucleic acid sequences (DNA and/or RNA). Most of them rely on the amplification of these nucleic acids by the polymerase chain reaction (PCR) technique. The majority of amplification techniques for diagnosis of microbe target the rRNA genes (rDNA). Comparing the sequences obtained to one another, and to those held in databases, allows phylogenetic relationships between microbes to be established. PCR-based techniques, denaturing gradient gel electrophoresis (DGGE), temporal temperature gra-dient gel electrophoresis (TTGE), single-stranded conformation polymorphism (SSCP), real-time quantitative PCR (qPCR) involve construction and analysis of 16S rRNA gene libraries, terminal restriction fragment length polymorphism (TRFLP), and a few others (Alegría et al., 2009; Ampe, ben Omar, Moizan, Wacher, & Guyot, 1999; Bokulich & Mills, 2012a; Carraro et al., 2011; Cocolin, Manzano, Cantoni, & Comi, 2001; Cocolin, Innocente, Biasutti, & Comi, 2004; Delbès, Ali-Mandjee, & Montel, 2007; Ercolini, Mauriello, Blaiotta, Moschetti, & Coppola, 2004; Gkatzionis, Yunita, Linforth, Dickinson, & Dodd, 2014; Randazzo, Torriani, Akkermans, de Vos, & Vaughan, 2002; Hu & Li, 2017). Of these, DGGE (qualitative/semiquantitative analysis) and qPCR (quan-titative analysis) have gained popularity to microbiologically characterize food environments and to analyze the course of food fermentations. This is due to the fact that they have made it possible to extensively decrease assay time and multiplex while maintaining a high level of sensitivity and specificity. Use of PCR-based methods has increased exponentially over the past two decades and attracted the attention of end-user laborato-ries even passed EC regulations and European Network of GMO Laboratories for food quality control. However, deviations have been observed with respect to different labs in terms of results. It may be due to the variation in the performance of PCR ther-mal cyclers; efficiencies of different polymerases enzymes; pres-ence of inhibitors in the samples, etc. Reproducing the reported PCR results has been very difficult for same sample univer-sally. Internationally recognized standard guidelines should be established to solve this issue (Hoorfar, 1999; Hoofer, 2003). Additionally, changes in microbial populations impose another level of challenge in context to dynamics of food fermentation, the monitoring of the growth of starter and adjunct cultures, and the fate of pathogen and spoiling microorganisms. A number of new microbial types with no cultured relatives—and occasion-ally of potential technological interest—have also been area of interest to be detected.

Next generation of PCR have shown developments in the form of digital PCR, LAMP, combining with other techniques like


capillary electrophoresis etc appears to over come all these short-commings (García-Canas et al., 2002). Additionally, use of recent techniques like commercial microfluidic CE system (LabChip) (Birch, Archard, Parkes, & McDowell, 2001; Burns, Shanahan, Valdivia, & Harris, 2003), modeling of optimal DNA chip design; microarray technology (Leimanis et al., 2006), using computers; and an anchored PCR primed from commonly found sequences of unknown microbe or GMO and use of other advanced methods of molecular electronics such as biosensors can provide promis-ing alternatives. Advances in various microarrays right from basic one to printed to suspended bead microarray and electronic micro array in multiple dimensions combined with PCR-amplified tar-gets and software algorithms, gene banks, metabolomics, and statistically tools have brought multifold rise in the performance parameters (fast multiplexing thousands of samples, with accu-racy and precision). Although a large number of modifications have been incorporated in the list of molecular techniques, there still exist many challenges and opportunities to improve the cur-rent technology for food pathogen detection. New targets are being associated with upcoming methods of target mining and enormously expanding GenBank.

Another level of unprecedented development is in the field of DNA sequencers, that is, next-generation sequencing. DNA sequencing has seen growth from Sanger’s method (1977), the first generations sequencing to most recent Next-Generation Sequencing (NGS) techniques. This recent explosion of newly developed highly improved versions of sequencing methods, that is, NGS techniques provide high-throughputs and produce thousands or even millions of sequences at the same time. These methods can be used for accurate identification of microbes that are difficult to culture or are present in trace amount/numbers. NGS has also realized to make it possible to prepare complete list of all microbial operons and genes present or being expressed under different study conditions. Therefore, NGS techniques have immense applications in the fields of microbial ecology, food eco-systems, clinical diagnosis, and food industries. NGS techniques have also promoted the emergence of new, high-throughput technologies, such as genomics, metagenomics, transcriptomics, and metatranscriptomics. As compared to contemporary culture-independent methods like PCRs and microarrays, the number of nucleic acid sequences analyzed by NGS techniques is exceed-ingly higher, allowing a deeper description of the microbial con-stituents of the ecosystems.

These technologies are being used in two substantially dif-ferent ways: sequencing total microbial nucleic acids (shotgun


sequencing) and gene-specific sequencing (targeted sequenc-ing). For the latter, segments of highly conserved DNA or cDNA sequences are first amplified by PCR using universal or group-spe-cific primers. Shotgun sequencing returns information far beyond that regarding phylogenetic composition, providing insights into the number and potential function of genes within the commu-nity (Solieri, Dakal, & Giudici, 2013; Wilmes, Simmons, Denef, & Banfield, 2009). Both shotgun and targeted techniques have already been used to study the microbiology of a series of foods and food fermentations, and pertinent reviews have recently been compiled (Bokulich and Mills, 2012b; Ercolini, 2013; Liu, 2011; Solieri et al., 2013). However, research in this area is so active that findings must be continually reviewed, and the current and potential applications of these constantly updated.

It is worth mentioning that recent most molecular techniques including Next-generation PCR, microarray, and sequencing are clearly convergence of overlapping/nonoverlapping fields of engineering, nanotechnology, and food science (Arora, 2018). Next generation of molecular techniques combined with Whole Metagenomic Sequencing (WMS) and Whole Genome Sequencing (WGS) has motivated researchers to achieve and realize detection of unrelated samples in one reaction/experiment while making it possible to the level of “lab-on-a-chip” or “point-of-care test-ing” technologies, which is fast, portable, sensitive, specific, and automated.

AcknowledgmentsWe are grateful to Prof. M. Jagdesh Kumar, Vice Chancellor, Jawaharlal Nehru

University, New Delhi, India Financial support received under the DST PURSE and UPoE-II is sincerely acknowledged.

Declaration of Competing InterestThe authors declare that they have no known competing

financial interests or personal relationships that could have appeared to influence the work reported in this chapter. Also, the views expressed in the chapter do not represent the views of the Company/Institute the authors belong to.

ReferencesAarts, H., van Rie, J. P., & Kok, E. J. (2002). Molecular diagnostics: current technology

and applications. Expert Review of Molecular Diagnostics, 2, 69–76. Ahmed, F. E. (2002). Detection of genetically modified organisms in foods. Trends

in Biotechnology, 20(5), 215–223.

http://refhub.elsevier.com/B978-0-12-813266-1.00005-X/ref5110





Alegría, A., Álvarez-Martín, P., Sacristán, N., Fernández, E., Del- gado, S., & Mayo, B. (2009). Diversity and evolution of majority microbial populations during manufacturing and ripening of Casín, a Spanish traditional, starter-free cheese made of raw cow’s milk. International Journal of Food Microbiology., 136, 44–51.

Aliyu, S. H., Aliyu, M. H., Salihu, H. M., Parmar, S., Jalal, H., & Curran, M. D. (2004). Rapid detection and quantitation of hepatitis B virus DNA by real-time PCR using a new fluorescent (FRET) detection system. Journal of Clinical Virology, 30, 191–195.

Ampe, F., ben Omar, N., Moizan, C., Wacher, C., & Guyot, J. P. (1999). Polyphasic study of the spatial distribution of microorganisms in Mexican pozol, a fermented maize dough, demonstrates the need for cultivation-independent methods to investigate traditional fermentations. Applied and Environmental Microbiology, 65, 5464–5473.

Angers-Loustau, A., Petrillo, M., Bonfini, L., et al. (2014). JRC GMO-Matrix: a web application to support genetically modified organisms detection strategies. BMC Bioinformatics, 15, 417.

Ardui, S., Ameur, A., Vermeesch, J. R., & Hestand, M. S. (2018). Single molecule real-time (SMRT) sequencing comes of age: applications and utilities for medical diagnostics. Nucleic Acids Research, 46(5), 2159–2168.

Armstrong, B., Stewart, M., & Mazumder, A. (2000). Suspension arrays for high throughput, multiplexed single nucleotide polymorphism genotyping. Cytometry, 40, 102–108.

Arnal, C., Ferre-Aubineau, V., Mignotte, B., Imbert-Marcille, B. M., & Billaudel, S. (1999). Quantification of hepatitis A virus in shellfish by competitive reverse transcription-PCR with coextraction of standard RNA. Applied and Environmental Microbiology, 65, 322–326.

Arora, K. (2018). Advances in Nano Based Biosensors for Food and Agriculture. In K. Gothandam, S. Ranjan, N. Dasgupta, C. Ramalingam, & E. Lichtfouse (Eds.), Nanotechnology, Food Security and Water Treatment. Environmental Chemistry for a Sustainable World (pp. 1–52). Cham: Springer ISBN: 978-3-319-70166-0.

Augustin, J. C., & Carlier, V. (2006). Review: Lessons from the organization of a proficiency testing program in food microbiology by interlaboratory comparison: Analytical methods in use, impact of methods on bacterial counts and measurement uncertainty of bacterial counts. Food Microbiology, 23, 1–38.

Bøving, M. K., Pedersen, L. N., & Moller, J. K. (2009). Eight-plex PCR and liquid-array detection of bacterial and viral pathogens in cerebrospinal fluid from patients with suspected meningitis. Journal of Clinical Microbiology, 47, 908–913.

Bahrdt, C., Krech, A. B., Wurz, A., & Wulff, D. (2010). Validation of a newly developed hexaplex real-time PCR assay for screening for presence of GMOs in food, feed and seed. Analytical and Bioanalytical Chemistry, 396(6), 2103–2112.

Barany, F. (1991a). Genetic disease detection and DNA amplification using cloned thermostable ligase. Proceedings of the National Academy of Sciences, 88, 189–193.

Barany, F. (1991b). The ligase chain reaction in a PCR world. PCR Methods Application, 1, 5–16.

Barbau-Piednoir, E., Lievens, A., Mbongolo-Mbella, G., et al. (2010). SYBR Green qPCR screening methods for the presence of ‘35S promoter’ and ‘NOS terminator’ elements in food and feed products. European Food Research and Technology, 230(3), 383–393.
























































Barringer, K., Orgel, L., Wahl, G., & Gingeras, T. R. (1990). Blunt-end and single-stranded ligations by Escherichia coli ligase: Influence on an in vitro amplification scheme. Gene, 89, 117–122.

Batt, C. A., Wagner, P., Wiedmann, M., Luo, J., & Gilbert, R. O. (1994). Detection of bovine leukocyte adhesion deficiency by nonisotopic ligase chain reaction. Animal Genetics, 25, 95–98.

Bayley, H. (2015). Nanopore sequencing: From imagination to reality. Clinical Chemistry, 61(1), 25–31.

Beans, C. (2017). Companies seek foods safety using a microbiome approach. Proceedings of the National Academy of Sciences, 114(51), 13306–13308.

Bej, A. K., Mahbubani, M. H., Miller, R., DiCesare, J. L., Haft, L., & Atlas, R. M. (1990). Multiplex PCR amplification and immobilized capture probes for detection of bacterial pathogens and indicators in water. Molecular and Cellular Probes, 4, 353–365.

Bej, A. K., McCarty, S. C., & Atlas, R. M. (1991). Detection of coliform bacteria and Escherichia coli by multiplex polymerase chain reaction: Comparison with defined substrate and plating methods for water quality monitoring. Applied and Environmental Microbiology, 57, 1473–1479.

Bhat, S., Herrmann, J., Armishaw, P., Corbisier, P., & Emslie, K. R. (2009). Single molecule detection in nanofluidic digital array enables accurate measurement of DNA copy number. Analytical and Bioanalytical Chemistry, 394(2), 457–467.

Birch, L., Archard, C. L., Parkes, H. C., & McDowell, D. G. (2001). Evaluation of LabChiptechnology for GMO analysis in food. Food Control, 12, 535–540.

Boerlin, P., Bannerman, E., Ischer, F., Rocurt, J., & Bille, J. (1995). Typing of Listeria monocytogenes: A comparison of random amplification of polymorphic DNA with 5 other methods. Research in Microbiology, 146, 35–49.

Bokulich, N. A., & Mills, D. A. (2012a). Differentiation of mixed lactic acid bacteria communities in beverage fermentations using targeted terminal restriction fragment length polymorphism. Food Microbiology, 31, 126–132.

Bokulich, N. A., & Mills, D. A. (2012b). Next-generation approaches to the microbial ecology of food fermentations. BMB Reports, 45, 377–389.

Bordoni, R., Germini, A., Mezzelani, A., Marchelli, R., & De Bellis, G. (2005). A microarray platform for parallel detection of five transgenic events in foods: A combined polymerase chain reaction–ligation detection reaction–universal array method. Journal of Agricultural and Food Chemistry, 53, 912–918.

Broeders, S. R. M., de Keersmaecker, S. C. J., & Roosens, N. H. C. (2012). How to deal with the upcoming challenges in GMO detection in food and feed. Journal of Biomedicine and Biotechnology, 2012(402418), 11.

Broeders, S., Papazova, N. Van den Bulcke, M., Roosens, N. 2012a. Development of a molecular platform for GMO detection in food, feed on the basis of ‘combinatory qPCR’ technology, in Polymerase Chain Reaction, chapter 18, pp. 363-404, InTech, Rijeka, Croatia.

Broeders, S., Fraiture, M. A., Vandermassen, E., et al. (2015). New trait-specific qualitative SYBR Green qPCR methods to expand the panel of GMO screening methods used in the CoSYPS. European Food Research and Technology, 241(2), 275–287.

Buermans, H. P. J., & den Dunnen, J. T. (2014). Next generation sequencing technology: advances and applications. Biochimica et Biophysica Acta: Molecular Basis of Disease, 1842(10), 1932–1941.

Burns, M., Shanahan, D., Valdivia, H., & Harris, N. (2003). Quantitative event-specific multiplex PCR detection of Roundup Ready soya using LabChip technology. European Food Research and Technology, 216, 428–433.




















































Burns, M. J., Burrell, A. M., & Foy, C. A. (2010). The applicability of digital PCR for the assessment of detection limits in GMO analysis. European Food Research and Technology, 231(3), 353–362.

Bustin, S. A., Benes, V., et al. (2005). Quantitative real-time RT-PCR - A perspective. Journal of Molecular Endocrinology, 34(3), 597–601.

Bustin, S. A. (2000). Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. Journal of Molecular Endocrinology, 25, 169–193.

Cargill, M., Altshuler, D., Ireland, J., Sklar, P., Ardlie, K., Patil, N., Shaw, N., Lane, C. R., Lim, E. P., Kalyanaraman, N., et al. (1999). Characterization of single-nucleotide polymorphisms in coding regions of human genes. Nature Genetics, 22, 231–238.

Carraro, L., Maifreni, M., Bartolomeoli, I., Martino, M. E., Novelli, E., Frigo, F., Marino, M., & Cardazzo, B. (2011). Comparison of culture- dependent and –independent methods for bacterial community monitoring during Montasio cheese manufacturing. Research Microbiology, 162, 231–239.

Cartwright, C. P. (1995). Polymerase chain reaction ribotyping: a “universal” approach? Journal of Infectious Diseases, 172, 1638–1639.

Carver, J. D. (1999). Dietary nucleotides: Effects on the immune and gastrointestinal systems. Acta Paediatrica, 88, 83–88.

Casas, N., Amarita, F., & de Maranon, I. M. (2007). Molecular methods for the detection and characterization of foodborne pathogens. International Journal of Food Microbiology, 120, 179–185.

Chamberlain, J. S., Gibbs, R. A., Gibbs, J. E., Ranier, P. N., Nguyen, & Caskey, C. T. (1988). Deletion screening of the Duchenne muscular dystrophy locus via multiplex DNA amplification. Nucleic Acids Research, 16, 11141–11156.

Chamberlain, J. S., Gibbs, R. A., Ranier, J. E., & Caskey, C. T. (1992). Detection of gene deletions using multiplex polymerase chain reactions. Methods in Molecular Biology, 9, 299–312.

Chan, A. B., & Fox, J. D. (1999). NASBA and other transcription-based amplification methods for research and diagnostic microbiology. Reviews in Medical Microbiology, 10, 185–196.

Chapela, M. J., Garrido-Maestu, A., & Cabado, A. G. (2015). Detection of foodborne pathogens by qPCR: A practical approach for food industry applications. Cogent Food & Agriculture, 1, 1–19 1013771.

Chien, A., Edgar, D. B., & Trela, J. M. (1976). Deoxyribonucleic acid polymerase from the extreme thermophile Thermus aquaticus. Journal of Bacteriology, 127, 1550–1557.

Christensen, H., Jorgensen, K., & Olsen, J. E. (1999). Differentiation of Campylobacter coli and C. jejuni by length and DNA sequence of the 16S–23S rRNA internal spacer region. Microbiology, 145, 99–105.

Churruca, E., Girbau, C., Martinez, I., Mateo, E., Alonso, R., & Fernandez-Astorga, A. (2007). Detection of Campylobacter jejuni and Campylobacter coli in chicken meat samples by real- time nucleic acid sequence-based amplification with molecular beacons. International Journal of Food Microbiology, 117, 85.

Cocolin, L., Manzano, M., Cantoni, C., & Comi, G. (2001). Denaturing gradient gel electrophoresis analysis of the 16S rRNA gene V1 region to monitor dynamic changes in the bacterial population during fermentation of Italian sausages. Applied and Environmental Microbiology, 67, 5113–5121.

Cocolin, L., Innocente, N., Biasutti, M., & Comi, G. (2004). The late blowing in cheese: A new molecular approach based on PCR and DGGE to study the microbial ecology of the alteration process. International Journal of Food Microbiology, 90, 83–91.
























































Codex Alimentarius Commission, 2004. Criteria for the methods for the detection and identification of foods derived from biotechnology. General approach and criteria for the methods. CX/MAS 04/10.

Cook, N. (2003). The use of NASBA for the detection of microbial pathogens in food and environmental samples. Journal of Microbiological Methods, 53, 165–174.

Corbisier, P. S., Bhat, S., Partis, L., Xie, V. R. D., & Emslie, K. R. (2010). Absolute quantification of genetically modified MON810 maize (Zea mays L.) by digital polymerase chain reaction. Analytical and Bioanalytical Chemistry, 396(6), 2143–2150.

Crutchfield, S., Kuchler, F., & Variyam, J. N. (1999). New federal policies and programs for food safety. Food Safety, 22, 2.

Cutler, D. J., Zwick, Michael E., Carrasquillo, Minerva M., Yohn, Christopher T., Tobin, Katherine P., Kashuk, Carl, Mathews, Debra J., Shah, Nila A., Eichler, Evan E., Warrington, Janet A., & Chakravarti, Aravinda (2001). High-throughput variation detection and genotyping using microarrays. Genome Research, 11, 1913–1925.

Czajka, J., Bsat, N., Piani, M., Russ, W., Sultana, K., Wiedman, M., Whitaker, J., & Batt (1993). Differentiation of Listeria monocytogens and Listeria innocua by 16S rRNA genes and intraspecies discrimination of Listeria monocytogenes strains by random amplified polymorphic DNA polymorphisms. Applied and Environmental Microbiology, 59, 304–308.

Dalma-Weiszhausz, D. D., Warrington, J., Tanimoto, E. Y., & Miyada, C. G. (2006). The Affymetrix GeneChip platform: an overview. Methods Enzymology, 410, 3–28.

GMO database, 2002. Agriculture and Biotechnology Strategies Canada inc. http://www.agbios.com.

De Baar, M. P., Timmermans, E. C., Bakker, M., de Rooij, E., van Gemen, B., & Goudsmit, J. (2001). One-tube real-time isothermal amplification assay to identify and distinguish human immunodeficiency virus type 1 subtypes A, B, and C and circulating recombinant forms AE and AG. Journal of Clinical Microbiology, 39, 1895–1902.

Delbès, C., Ali-Mandjee, L., & Montel, M. C. (2007). Monitoring bacterial communities in raw milk and cheese by culture-dependent and -independent 16S rRNA gene-based analysis. Applied Environmental Microbiology, 73, 1882–1891.

Deng, J., Zheng, Y., Zhao, R., Wright, P. F., Stratton, C. W., & Tang, Y. W. (2009). Culture versus polymerase chain reaction for the etiologic diagnosis of community-acquired pneumonia in antibiotic-pretreated pediatric patients. Pediatric Infectious Disease Journal, 28, 53–55.

Di, H., Shi, L., Shen, H., et al. (2014). Rapid detection of genetically modified ingredients in soybean products by real-time loop-mediated isothermal amplification. Journal of Food and Nutrition Research, 2(7), 363–368.

Doerfler, W. (2000). Foreign DNA in Mammalian Systems. Weinheim: Wiley-VCH 1-177.

Domingo, J. L. (2007). Toxicity studies of genetically modified plants. a review of the published literature. Critical Reviews in Food Science and Nutrition, 47, 721–733.

Dong, W., Yang, L., Shen, K., Kim, B., Kleter, G. A., Marvin, H. J. P., Guo, R., Liang, W., & Zhang, D. (2008). GMDD: a database of GMO detection methods. BMC Bioinformatics, 9, 260.

Dong, L., Meng, Y., Sui, Z., Wang, J., Wu, L., & Fu, B. (2015). Comparison of four digital PCR platforms for accurate quantification of DNA copy number of a certified plasmid DNA reference material. Scientific Reports, 25(5), 13174.























http://www.agbios.com





























Doolittle, W. F., & Pace, N. R. (1971). Transcriptional organization of the ribosomal RNA cistrons in Escherichia coli. Proceedings of the National Academy of Sciences USA, 68, 1786–1790.

Dube, S., Qin, J., & Ramakrishnan, R. (2008). Mathematical analysis of copy number variation in a DNA sample using digital PCR on a nanofluidic device. PLoS ONE, 3(8), e2876.

Dunbar, S. A. (2006). Applications of Luminex xMAP technology for rapid, high-throughput multiplexed nucleic acid detection. Clinica Chimica Acta, 363, 71–82.

EBI: Next Generation Sequencing Practical Course, https://www.ebi.ac.uk/training/online/course/ebi-next-generation-sequencing-practical-course.

EC Regulation, 2003. Regulation (EC) No 1830/2003 of 22/09/2003 concerning the traceability and labelling of genetically modified organisms and the traceability of food and feed products produced from genetically modified organisms and amending directive 2001/18/EC.

Regulation (EC) No 1829/2003 of the European Parliament and of the Council of 22 September 2003 on Genetically Modified Food and Feed Official Journal of European Union.

Regulation (EC) No 882/2004 of the European Parliament and of the Council of 29 April 2004, Official Journal of the European Union.

Regulation (EC) No 619/2011 of the European Parliament and of the Council of 24 June 2011, Official Journal of the European Union.

Edelstein, R. L., Tamanaha, C. R., Sheehan, P. E., Miller, M. M., Baselt, D. R., Whitman, L. J., & Colton, R. J. (2000). The BARC biosensor applied to the detection of biological warfare agents. Biosensor Bioelectron, 14, 805–813.

Edwards, K., Logan, J., & Saunders, N. (2004). Real-Time PCR: An essential guide. UK: Horizon Bioscience 1-346.

Ehrenreich, A. (2006). DNA microarray technology for the microbiologist: an overview. Applied Microbiology and Biotechnology, 73, 255–273.

Emons, H. (2010). GMO analysis – a complex and challenging undertaking. Analytical and Bioanalytical Chemistry, 396, 1949–1950.

Ercolini, D., Mauriello, G., Blaiotta, G., Moschetti, G., & Coppola, S. (2004). PCR-DGGE fingerprints of microbial succession during a manufacture of traditional water buffalo mozzarella cheese. Journal of Applied Microbiology, 96, 263–270.

Ercolini, D. (2013). High-throughput sequencing and metagenomics: moving forward in the culture-independent analysis of food microbial ecology. Applied and Environmental Microbiology, 79, 3148–3155.

Erlich, H. A., Gelfand, D., & Sninsky, J. J. (1991). Recent advances in the polymerase chain reaction. Science, 252, 1643–1650.

Ewen, S. W., & Pusztai, A. (1999). Effect of diets containing genetically modified potatoes expressing Galanthus nivalis lectin on rat small intestine. Lancet, 354, 1353–1354.

Fan, J. B., Hu, S. X., Craumer, W. C., & Barker, D. L. (2005). Bead Array-based solutions for enabling the promise of pharmacogenomics. BioTechniques, 39, 583–588.

Fan, J. B., Gunderson, K. L., Bibikova, M., ……, & Barker, D. (2006). Illumina universal bead arrays. Methods Enzymology, 410, 57–73.

Fares, N. H., & El-Sayed, A. K. (1998). Fine structural changes in the ileum of mice fed on delta- endotoxin-treated potatoes and transgenic potatoes. Natural Toxins, 6, 219–233.

Feero, W. G., Wang, J., Barany, F., Zhou, J., Todorovic, S. M., Conwit, R., Galloway, G., Hausmanowa- Petrusewicz, I., Fidzianska, A., Arahata, K., Wessel, H. B., Wadelius, C., Marks, H. G., Hartlage, P., Hayakawa, H., & Hoffman, E. P. (1993).










https://www.ebi.ac.uk/training/online/course/ebi-next-generation-sequencing-practical-course

https://www.ebi.ac.uk/training/online/course/ebi-next-generation-sequencing-practical-course


































Hyperkalemic periodic paralysis: Rapid molecular diagnosis and relationship of genotype to phenotype in 12 families. Neurology, 43, 668–673.

Feil, E. J., & Spratt, B. G. (2001). Recombination and the population structures of bacterial pathogens. Annual Review of Microbiology, 55, 561–590.

Paul D. Fey, Pulsed-Field Gel Electrophoresis (PFGE): The Molecular Epidemiologists Tool. NPHL. www.nphl.org/documents/PFGE.pdf.

Fodor, S. P., Read, J. L., Pirrung, M. C., Stryer, L., Lu, A. T., & Solas, D. (1991). Light-directed, spatially addressable parallel chemical synthesis. Science, 251, 767–773.

Fox, G. E., Stackebrandt, E., Hespell, R. B., Gibson, J., Maniloff, J., Dyer, T. A., Wolfe, R. S., Balch, W. E., Tanner, R. S., Magrum, L. J., Zablen, L. B., Blakemore, R., Gupta, R., Bonen, L., Lewis, B. J., Stahl, D. A., Luehrsen, K. R., Chen, K. N., & Woese, C. R. (1980). The phylogeny of prokaryotes. Science, 209, 457–463.

Fraiture, M. -A., Herman, P., Taverniers, I., De Loose, M., Deforce, D., & Roosens, N. H. (2014). An innovative and integrated approach based on DNA walking to identify unauthorised GMOs. Food Chemistry, 147, 60–69.

Fraiture, M. -A., Herman, P., Taverniers, I., et al. (2015). Validation of a sensitive DNA walking strategy to characterise unauthorised GMOs using model food matrices mimicking common rice products. Food Chemistry, 173, 1259–1265.

Gannon, V. P., King, R. K., Kim, J. Y., & Gotsteyn Thomas, E. J. (1992). Rapid and sensitive method for the detection of Shiga-like toxin producing bacteria in ground beef using the polymerase chain reaction. Applied and Environmental Microbiology., 8, 3809–3815.

García-Cañas, V., Gonzalez, R., & Cifuentes, A. (2002). Detection of genetically modified organisms in foods by dna amplification techniques. Journal of Separation Science, 25, 1–47.

Garcıa-Canas, V., Gonzalez, R., & Cifuentes, A. (2004). The combined use of molecular techniques and capillary electrophoresis in food analysis. Trends in Analytical Chemistry, 23(9), 637–642.

Germini, A., Rossi, S., Zanetti, A., Corradini, R., Fogher, C., & Marchelli, R. (2005). Development of a peptide nucleic acid array platform for the detection of genetically modified organisms in food. Journal of Agricultural and Food Chemistry, 53, 3958–3962.

Gibbs, R. A., Chamberlain, J. S., & Caskey, C. T. (1989). Diagnosis of new mutation diseases using the polymerase chain reaction. The polymerase chain reaction: Principles and Applications. New York: Stockton Press 171-192.

Gibson, U. E., Heid, C. A., & Williams, P. M. (1996). A novel method for real time quantitative RT-PCR. Genome Research, 6, 995–1001.

Gilgen, M., Wegmuller, B., Burkhalter, P., Buhler, H. P., Muller, U., Luthy, J., & Candrian, U. (1995). Reverse transcription PCR to detect enteroviruses in surface water. Applied and Environmental Microbiology, 61, 1226–1231.

Giraffa, G., & Carminati, D. (2008). Molecular techniques in food fermentation: Principles and applications. Food Microbiology and Food Safety, 1–30.

Gkatzionis, K., Yunita, D., Linforth, R. S., Dickinson, M., & Dodd, C. E. (2014). Diversity and activities of yeasts from different parts of a Stil ton cheese. International Journal of Food Microbiology, 177, 109–116.

GM FOOD, 2010. http://en.wikipedia.org/wiki/Genetically_modified_food. Genetically modified food. December 06, 2010.

Grelewska-Nowotko, K., Żurawska-Zajfert, M., Żmijewska, E., & Sowa, S. (2018). Optimization and Verification of Droplet Digital PCR Even-Specific Methods for the Quantification of GM Maize DAS1507 and NK603. Applied Biochemistry and Biotechnology, 185(1), 207–220.

Grimont, F., & Grimont, P. A. (1986). Ribosomal ribonucleic acid gene restriction patterns as potential taxonomic tools. Annales de l Institut Pasteur Microbiologie, 137B, 165–175.












































http://en.wikipedia.org/wiki/Genetically_modified_food









Guo, J., Yang, L., Liu, X., Zhang, H., Qian, B., & Zhang, D. (2009). Applicability of the Chymopapain Gene Used as Endogenous Reference Gene for Transgenic Huanong No. 1Papaya Detection. Journal of Agricultural and Food Chemistry, 57(15), 6502–6509.

Gurtler, V., & Barrie, H. D. (1995). Typing of Staphylococcus aureus strains by PCR- amplification of variable-length 16S–23S rDNA spacer regions: characterization of spacer sequences. Microbiology, 141, 1255–1265.

Gurtler, V., & Stanisich, V. A. (1996). New approaches to typing and identification of bacteria using the 16S-23S rDNA spacer region. Microbiology, 142, 3–16.

Halushka, M. K., Fan, J. B., Bentley, K., Hsie, L., Shen, N., Weder, A., Cooper, R., Lipshutz, R., & Chakravarti, A. (1999). Patterns of single-nucleotide polymorphisms in candidate genes for blood-pressure homeostasis. Nature Genetics, 22, 239–247.

Heid, C. A., Stevens, J., Livak, K. J., & Williams, P. M. (1996). Real time quantitative PCR. Genome Research, 6, 986–994.

Heide, B. R., Drømtorp, S. M., Rudi, K., Heir, E., & Holck, A. L. (2008a). Determination of eight genetically modified maize events by quantitative, multiplex PCR and fluorescence capillary gel electrophoresis. European Food Research and Technology, 227(4), 1125–1137.

Heide, B. R., Heir, E., & Holck, A. (2008b). Detection of eight GMO maize events by qualitative, multiplex PCR and fluorescence capillary gel electrophoresis. European Food Research and Technology, 227(2), 527–535.

Heim, A., Grumbach, I. M., Zeuke, S., & Top, B. (1998). Highly sensitive detection of gene expression of an intronless gene: amplification of mRNA, but not genomic DNA by nucleic acid sequence based amplification (NASBA). Nucleic Acids Research, 26, 2250–2251.

Hernández, M., Rodríguez-Lázaro, D., Esteve, T., Prat, S., & Pla, M. (2003). Development of melting temperature-based SYBR Green I polymerase chain reaction methods for multiplex genetically modified organism detection. Anal Biochemistry, 323, 164–170.

Hewitt, J., & Greening, G. E. (2006). Evaluation of murine norovirus as a surrogate for human norovirus and hepatitis A virus in heat inactivation studies. Journal of Food Protection., 69, 2217–2223.

Hibbitts, S., Rahman, A., John, R., Westmoreland, D., & Fox, J. D. (2003). Development and evaluation of NucliSens basic kit NASBA for diagnosis of parainfluenza virus infection with ‘end-point’ and ‘real-time’ detection. Journal of Virological Methods, 108, 145–155.

Higuchi, R., Fockler, C., Dollinger, G., & Watson, R. (1993). Kinetic PCR analysis: Real-time monitoring of DNA amplification reactions. BioTechnology, 11, 1026–1030.

Holingworth, R. M., Bjeldanes, L. F., Bolger, M., Syngenta, I. K., Meade, B. J., Taylor, S. L., & Wallace, K. B. (2003). The safety of genetically modified foods produced through biotechnology. Toxicological Sciences, 71, 2–8.

Holmes, B. 2010. “Altered animals: Creatures with bonus features”. New Scientist.http://www.newscientist.com/article/mg20727680.300-altered-animals-creatures- with bonus-features.html. (March, 2011).

Holst-Jensen, A., Rønning, S. B., Løvseth, A., & Berdal, K. G. (2003). PCR technology for screening and quantification of genetically modified organisms (GMOs). Analytical and Bioanalytical Chemistry, 375, 985–993.

Hoofer, J., Malorny, B., Abdulmawjood, A., Cook, N., Wanger, M., & Fach, P. (2003). Practical considerations in design of internal amplification controls for diagnostic PCR assays. Journal of Clinical Microbiology, 42, 1863–1868.

Hoorfar, J. (1999). EU seeking to validate and standardize PCR testing of food pathogens. ASM News, 65, 799.

Horan, P. K., & Wheeless, L. L., Jr. (1977). Quantitative single cell analysis and sorting. Science, 198, 149–157.











































http://www.newscientist.com/article/mg20727680












Houde, A., Guevremont, E., Poitras, E., Leblanc, D., Ward, P., Simard, C., & Trottier, Y. L. (2007). Comparative evaluation of new TaqMan real-time assays for the detection of hepatitis A virus. Journal of Virological Methods, 140, 80.

Hu, L., & Li, B. (2017). Recent and the latest developments in rapid and efficient detection of salmonella in food and water. Advanced Techniques in Biology & Medicine, 5, 244.

Huggett, J. F., Foy, C. A., Benes, V., Emslie, K., Garson, J. A., Haynes, R., & Bustin, S. A. (2013). The digital MIQE guidelines: Minimum information for publication of quantitative digital PCR experiments. Clinical Chemistry, 59, 892–902.

Hughes, T., Mao, M., Jones, A., et al. (2001). Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer. Nature Biotechnology, 19, 342–347.

Hunt, M. 2006. Real time PCR tutorial - Copyright 2006, The Board of Trustees of the University of South Carolina.

Imai, M., Ninomiya, A., Minekawa, H., Notomi, T., Ischzaki, T., VanTu, P., Tien, N., Tashiro, M., & Odagiri, T. (2007). Rapid diagnosis of H5N1 avian influenza virus infection by newly developed influenza H5 hemagglutinin gene-specific loop-mediated isothermal amplification method. Journal of Virological Methods, 141, 173–180.

ISAAA, 2010. (International Service for the Acquisition of Agri-biotech Application) Global Status of Commercialized Biotech/GM Crops: Brief 42.

Iwasaki, M., Yonekawa, T., Otuska, K., Suzuki, W., Nagamine, K., Hase, K., Horigome, T., Notomi, T., & Kanda, H. (2003). Validation of the loop-mediated isothermal amplification method for single nucleotide polymorphism genotyping with whole blood. Genome Letter, 2, 119–126.

Järvinen, A. K., Laakso, S., Piiparinen, P., Aittakorpi, A., Lindfors, M., Huopaniemi, L., Piiparinen, H., & Mäki, M. (2009). Rapid identification of bacterial pathogens using a PCR- and microarray-based assay. BMC Microbiology, 9, 161.

Jayarao, B. M., Dore, J. J., Jr., Baumbach, G. A., Matthews, K. R., & Oliver, S. P. (1991). Differentiation of Streptococcus uberis from Streptococcus parauberis by polymerase chain reaction and restriction fragment length polymorphism analysis of 16S ribosomal DNA. Journal of Clinical Microbiology, 29, 2774–2778.

JCR GMO METHODS, http://gmo-crl.jrc.ec.europa.eu/gmomethods/.Köppel, R., & Bucher, T. (2015). Rapid establishment of droplet digital PCR for

quantitative GMO analysis. European Food Research and Technology, 241(3), 427–439.

Köppel, R., Bucher, T., Frei, A., & Waiblinger, H. U. (2015). Droplet digital PCR versus multiplex real-time PCR method for the detection and quantification of DNA from the four transgenic soy traits MON87769, MON87708, MON87705 and FG72, and lectin. European Food Research and Technology, 241(4), 521–527.

Kalin, I., Shephard, S., & Candrian, U. (1992). Evaluation of the ligase chain reaction (LCR) for the detection of point mutations. Mutation Research, 283, 119–123.

Kalogianni, D. P., Elenis, D. S., Christopoulos, T. K., & Ioannou, P. C. (2007). Multiplex quantitative competitive polymerase chain reaction based on a multianalyte hybridization assay performed on spectrally encoded microspheres. Analytical Chemistry, 79, 6655–6661.

Kaltenboek, B., Kansoulas, K. G., & Storz, J. (1992). Two-step polymerase chain reactions and restriction endonuclease analyses detect and differentiate ompA DNA of the Chlamydia spp. Journal of Clinical Microbiology, 30, 1098–1104.

Karl, V., Voelkerding, K. V., Shale Dames, S., Jacob, D., & Durtschi, J. D. (2010). Next Generation Sequencing for Clinical Diagnostics-Principles and Application to





















































Targeted Resequencing for Hypertrophic Cardiomyopathy, A Paper from the 2009 William Beaumont Hospital Symposium on Molecular Pathology. Journal of Molecular Diagnostics, 12(5), 539–551.

Karlen, Y., McNair, A., et al. (2007). Statistical significance of quantitative PCR. BMC Bioinformatics, 8, 131.

Karleson, F., Steen, H., & Nesland, J. (1995). SYBR green I DNA staining increases the detection sensitivity of viruses by polymerase chain reaction. Journal of Virological Methods, 55, 153–156.

Kchouk, M., Gibrat, J. F., & Elloumi, M. (2017). Generations of sequencing technolo-gies: from first to next generation. Biology and Medicine (Aligarh), 9, 395.

Khodakov, D. A., Zakharova, N. V., Gryadunov, D. A., Filatov, F. P., Zasedatelev, A. S., & Mikhailovich, V. M. (2008). An oligonucleotide microarray for multiplex real-time PCR identification of HIV-1, HBV, and HCV. BioTechniques, 44 241–246, 248.

Kievits, T. (1991). NASBA. Isothermal enzymatic in vitro nucleic acid amplification optimized for the diagnosis of HIV-1 infection. Journal of Virological Methods, 35, 273–286.

Kim, D., Kim, S. R., Kwon, K. S., Lee, J. W., & Oh, M. J. (2008). Detection of hepatitis a virus from oyster by nested PCR using efficient extraction and concentration method. Journal of Microbiology, 46, 436–440.

Kim, W. (2012). Application of metagenomic techniques: Understanding the unrevealed human microbiota and explaining the in clinical infectious diseases. Journal of Bacteriology and Virology, 42(4), 263–275.

Kitchin, P. A., Szotyori, Z., Fromholc, C., & Almond, N. (1990). Avoidance of PCR false positives. Nature, 344, 201.

Klein, P. G., & Kuneja, V. J. (1997). Sensitive detection of viable Listeria monocytogenes by reverse trascription-PCR. Applied and Environmental Microbiology, 63, 4441–4448.

Klemsdal, S. S., & Elen, O. (2006). Development of a highly sensitive nested-PCR method using a single closed tube for detection of Fusarium culmorum in cereal samples. Letters in Applied Microbiology, 42, 544–548.

Kok, E. J., & Kuiper, H. A. (2003). Comparative safety assessment for biotech crops. Trends in Biotechnology, 21, 439–444.

Kolbert, C. P., & Persing, D. H. (1999). Ribosomal DNA sequencing as a tool for identification of bacterial pathogens. Current Opinion in Microbiology., 2(3), 299–305.

Kostman, J. R., Edlind, T. D., LiPuma, J. J., & Stull, T. L. (1992). Molecular epidemiology of Pseudomonas cepacia determined by polymerase chain reaction ribotyping. Journal of Clinical Microbiology, 30, 2084–2087.

Kostman, J. R., Alden, M. B., Mair, M., Edlind, T. D., LiPuma, J. J., Bouchet, & Stull, T. L. (1995). A universal approach to bacterial molecular epidemiology by polymerase chain reaction ribotyping. Journal of Infectious Diseases, 171, 204–208.

Kreil, D. P., Russell, R. R., & Russell, S. (2006). Microarray oligonucleotide probes. Methods Enzymology, 410, 73–98.

Krunic, N., Yager, T. D., Himsworth, D., Merante, F., Yaghoubian, S., & Janeczko, R. (2007). xTAG RVP assay: analytical and clinical performance. Journal of Clinical Virology, 40(Suppl. 1), S39–S46.

Kumar, V., & Arora, K. (2020). Trends in nano-inspired biosensors for plants. Materials Science for Energy Technologies, 3, 255–273.

Kwok, S., & Higuchi, R. (1989). Avoiding false positives with PCR. Nature, 339, 237–238.

Lakicevic, B., Nastasijevic, I., & Dimitrijevic, M. (2017). Whole genome sequencing: an efficient approach to ensuring food safety. IOP Conf. Ser.: Earth Environ. Sci., 85, 012052.
























































Lambertz, S. T., Nilsson, C., & Hallanvuo, S. (2008). TaqMan-Based Real-Time PCR Method for Detection of Yersinia pseudotuberculosis in Food. Applied and Environmental Microbiology, 74, 6465–6469.

Lander, E. S. (1999). Advantages and limitations of microarray technology in human cancer. Natural Genetics, 21, 3–4.

Lawrence, L., & Gilmour, A. (1995). Characterization of Listeria monocytogenes isolated from poultry products and from poultry-processing environment by random amplification of polymorphic DNA and multilocus enzyme electrophoresis. Applied and Environmental Microbiology, 61, 2139–2144.

Lawrence, L., Harvey, J., & Gilmour, A. (1993). Development of a random amplification of polymorphic DNA typing method for Listeria monocytogenes. Applied and Environmental Microbiology, 59, 3117–3119.

Leimanis, S., Hernandez, M., Fernandez, S., Boyer, F., Burns, M., Bruderer, S., Glouden, T., Harris, N., Kaeppeli, O., Philip, P., Pla, M., Puigdomenech, P., Vaitilingom, M., Bertheau, Y., & Remacle, J. (2006). A microarray-based detection system for genetically modified (GM) food ingredients. Plant Molecular Biology, 61, 123–139.

Leonard, P. (2003). Advances in biosensors for detection of pathogens in food and water. Enzyme and Microbial Technology, 32, 3–13.

Leone, G., van Schijndel, H., van Gemen, B., Kramer, F. R., & Schoen, C. D. (1998). Molecular beacon probes combined with amplification by NASBA enable homogeneous, real-time detection of RNA. Nucleic Acids Research, 26, 2150–2155.

Liang, C., van Dijk, J. P., Scholtens, I. M. J., et al. (2014). Detecting authorized and unauthorized genetically modified organisms containing vip3A by real-time PCR and next- generation sequencing. Analytical and Bioanalytical Chemistry, 406(11), 2603–2611.

Lim, A., Eileen, T., Dimalanta, Konstantinos, D., Potamousis, Galex, Y., Jennifer, A., Chunhong, T., Jieyi, L., Rong, Q., John, S., Arvind, R., Nicole, T., Perna, Guy, P., Valerie, B., Bob, M., Jeremiah, H., Frederick, R., Blattner, Thomas S. A., Bhubaneswar, M., & David, C. S. (2001). Shotgun optical maps of the whole Escherichia coli O157:H7 genome. Genome Research, 11, 1584–1593.

Lin, B., Blaney, K. M., Malanoski, A. P., Ligler, A. G., Schnur, J. M., Metzgar, D., Russell, K. L., & Stenger, D. A. (2007). Using a resequencing microarray as a multiple respiratory pathogen detection assay. Journal of Clinical Microbiology, 45, 443–452.

Lin, B., Malanoski, A. P., Wang, Z., & Stenger, D. A. (2009). Universal detection and identification of avian influenza virus by use of resequencing microarrays. Journal of Clinical Microbiology, 47, 988–993.

Liu, G. E. (2011). Recent applications of DNA sequencing technologies in food, nutrition and agriculture. Recent Patents Food Nutr. Agri-cult., 3: 187-191.

Magi, A., Semeraro, R., Mingrino, A., Giusti, B., & D’Aurizio, R. (2017). Nanopore sequencing data analysis: state of the art, applications and challenges. Brief Bioinformatics 2017 Jun 16.

Maidak, B. L., Olsen, G. J., Larsen, N., Overbeek, R., McCaughey, M. J., & Woese, C. R. (1997). The RDP (Ribosomal Database Project). Nucleic Acids Research, 25, 109–111.

Maiden, M. C., Bygraves, J. A., Feil, E., Morelli, G., Russell, J. E., Urwin, R., Zhang, Q., Zhou, J., Zurth, K., Caugant, D. A., Feavers, I. M., Achtman, M., & Spratt, B. G. (1998). Multilocus sequence typing: a portable approach to the identification of clones within populations of pathogenic microorganisms. Proceedings of the National Academy of Sciences USA., 95, 3140–3145.

Marmiroli, N., Maestri, E., Gullì, M., Malcevschi, A., Peano, C., Bordoni, C., Bellis, G. (2008). Methods for detection of GMOs in food and feed. Analytical and Bioanalytical Chemistry. 392, 369–384.



















































Marvropoulou, A. K., Koraki, T., Ioannou, P. C., & Christopoulos, T. K. (2005). High-throughput double quantitative competitive polymerase chain reaction for determination of genetically modified organisms. Analytical Chemistry, 77, 4785–4791.

Mayo, B., Rachid, C. T. C. C., Alegría, A., Leite, A. M. O., Peixoto, R. S., & Delgado, S. (2014). Impact of Next Generation Sequencing Techniques in Food Microbiology. Current Genomics, 15, 293–309.

McLoughlin, K. S. (2011). Microarrays for pathogen detection and analysis briefings. Functional Genomics, 10(6), 342–353.

Merante, F., Yaghoubian, S., & Janeczko, R. (2007). Principles of the xTAG respiratory viral panel assay (RVP assay). Journal of Clinical Virology, 40(Suppl. 1), S31–S35.

Miller, M. B., & Tang, Y. W. (2009). Basic Concepts of Microarrays and Potential Applications in Clinical Microbiology. Clinical Microbiology Reviews, 611–633.

Modrich, P., Anraku, Y., & Lehman, I. R. (1973). Deoxyribonucleic acid ligase: Isolation and physical characterization of the homogeneous enzyme from Escherichia coli. Journal of Biological Chemistry, 248, 7495–7501.

Moore, C., Hibbitts, S., Owen, N., Corden, S. A., Harrison, G., Fox, J., Gelder, C., & Westmoreland, D. (2004). Development and evaluation of a real-time nucleic acid sequence based amplification assay for rapid detection of influenza A. Journal of Medical Virology, 74, 619–628.

Mori, Y., Nagamine, K., Tomita, N., & Notomi, T. (2001). Detection of loop-mediated isothermal amplification by turbidity derived from magnesium pyrophosphate formation. Biochemical and Biophysical Research Communications, 289, 150–154.

Mullis, K. B. (1990). The unusual origin of the polymerase chain reaction. Scientific American, 4, 36–48.

Myers, R. M., Maniatis, T., & Lerman, L. S. (1987). Detection and localization of single base pair changes by denaturing gradient gel electrophoresis. Methods in Enzymology, 155, 501.

Myint, M. S., Johnson, Y. J., Tablante, N. L., & Heckert, R. A. (2006). The effect of pre-enrichment protocol on the sensitivity and specificity of PCR for detection of naturally contaminated Salmonella in raw poultry compared to conventional culture a Short communication. Food Microbiology, 23, 599–604.

Nadal, A., Coll, A., La Paz, J. L., Esteve, T., & Pla, M. (2006). A new PCR-CGE (size and color) method for simultaneous detection of genetically modified maize events. Electrophoresis, 27, 3879–3888.

Nagamine, K., Watanabe, K., Ohtsuka, K., Hase, T., & Notomi, T. (2001). Loop-mediated isothermal amplification reaction using a non denatured template. Clinical Chemistry, 47, 1742–1743.

Nagamine, K., Kuzuhara, Y., & Notomi, T. (2002). Isolation of single-stranded DNA from loop- mediated isothermal amplification products. Biochemical and Biophysical Research Communications, 290, 1195–1198.

Nam, H. M., Srinivasan, V., Murinda, S. E., & Oliver, S. P. (2005). Prevalence of antimicrobial resistance genes in Listeria monocytogenes isolated from dairy farms. Foodborne Pathogens and Disease., 2(3), 201–211.

Nanogen system. http://www.nanogen.com/technologies/microarray/ (December, 2010).

Neoh, H. M., Tan, X. E., Sapri, H. F., & Tan, T. L. (2019). Pulsed-field gel electrophoresis (PFGE): A review of the “gold standard” for bacteria typing and current alternatives. Infection, Genetics and Evolution, 74, 103935.

Newell, D. G., Koopmans, M., Verhoef, L., Duizer, E., Aidara-Kane, A., Sprong, H., Opsteegh, M., Langelaar, M., Threfall, J., Scheutz, F., van der Giessen, J., & Kruse, H. (2010). Food-borne diseases - the challenges of 20 years ago still















































http://www.nanogen.com/technologies/microarray/








persist while new ones continue to emerge. International Journal of Food Microbiology, 30, 139.

Nolan, J. P., & Sklar, L. A. (2002). Suspension array technology: evolution of the flat-array paradigm. Trends Biotechnology, 20, 9–12.

Notomi, T., Okayama, H., Masubuchi, H., Yonekawa, T., Watanabe, K., Amino, N., & Hase, T. (2000). Loop mediated isothermal amplification of DNA. Nucleic Acids Research, 28(12), e63 (i-vii).

Nugen’s Ovation™ RNA Amplification and Labeling Systems. http://www.nugeninc.com/nugen/index.cfm/products/ (February, 2011).

OECD (Organization for Economic Co-operation and Development) Paris, 1993. Safety Evaluation of Foods Derived by Modern Biotechnology: Concepts and Principles. http://www.oecd.org/pdf/ M00034000/M00034525. (February, 2011).

Oliphant, A., Barker, D. L., Stuelpnagel, J. R., & Chee, M. S. (2002). Bead Array technology: enabling an accurate, cost-effective approach to high-throughput genotyping. BioTechniques 2002(Suppl.), 56-58, 60–61.

Oniciuc, E. A., Likotrafiti, E., Alvarez-Molina, A., Prieto, M., Santos, J. A., & Alvarez-Ordóñez, A. (2018). The Present and Future of Whole Genome Sequencing (WGS) and Whole Metagenome Sequencing (WMS) for Surveillance of Antimicrobial Resistant Microorganisms and Antimicrobial Resistance Genes across the Food Chain. Genes 2018, 9, 268.

Oniciuc, E. A., Likotrafiti, E., Alvarez-Molina, A., Prieto, M., Santos, J. A., & Alvarez-Ordóñez, A. (2018). The Present and Future of Whole Genome Sequencing (WGS) and Whole Metagenome Sequencing (WMS) for Surveillance of Antimicrobial Resistant Microorganisms and Antimicrobial Resistance Genes across the Food Chain. Genes (Basel)., 22; 9(5).

Onishi, M., Matsuoka, T., Kodama, T., Kashiwaba, K., Futo, S., Akiyama, H., Maitani, T., Furui, S., Oguchi, T., & Hino, A. (2005). Development of a multiplex polymerase chain reaction method for simultaneous detection of eight events of genetically modified maize. Journal of Agricultural and Food Chemistry, 53, 9713–9721.

Orbach, M. J., Vollrath, D., Davis, R. W., & Yanofsky, C. (1988). An electrophoretic karyotype of Neurospora crassa. Molecular and Cellular Biology, 8, 1469–1473.

Pace, N. R., Olsen, G. J., & Woese, C. R. (1986). Ribosomal RNA phylogeny and the primary lines of evolutionary descent. Cell, 45, 325–326.

Patel, R., Torres, R. J., & Rosset, P. (2005). Genetic engineering in agriculture and corporate engineering in public debate: risk, public relations, and public debate over genetically modified crops. International Journal of Occupational and Environmental Health., 11, 428–436.

Paun, O., & P, Schönswetter (2012). Amplified Fragment Length Polymorphism (AFLP) - an invaluable fingerprinting technique for genomic, transcriptomic and epigenetic studies. Methods Mol Biol, 862, 75–87.

Pavlic, M. M., & Griffiths, W. (2009). Principles, applications, and limitations of automated ribotyping as a rapid method in food safety. Foodborne Pathogens and Disease, 6, 1047–1055.

Peano, C., Bordoni, R., Gulli, M., Mezzelani, A., Samson, M. C., De Bellis, G., & Marmiroli, N. (2005). Multiplex polymerase chain reaction and ligation detection reaction/universal array technology for the traceability of genetically modified organisms in foods. Analytical Biochemistry, 346, 90–100.

Pearson, B. M., & McKee, R. A. (1992). Rapid identification of Saccharomyces cerevisiae, Zygosaccharomyces bailii and Zygosaccharomyces rouxii. International Journal of Food Microbiology, 16, 63–67.

Pease, A., Solas, D., Fodor, S., et al. (1994). Light-generated oligo-nucleotide arrays for rapid DNA sequence analysis. Proceedings of the National Academy of Sciences of the United States of America, 91, 5022–5026.








http://www.nugeninc.com/nugen/index.cfm/products/

http://www.nugeninc.com/nugen/index.cfm/products/

http://www.oecd.org/pdf/












































PN- ISO/17025:2005, PN-EN ISO/IEC 17025:2005, General requirements for the competence of testing and calibration laboratorios,.,

Porcellato, D., Narvhus, J., & Skeie, S. B. (2016). Detection and quantification of Bacillus cereus group in milk by droplet digital PCR. Journal of Microbiological Methods, 127, 1–6.

Prediger I., Digital PCR (dPCR)—What is it and why use it?, Published Oct 21, 2013, Revised/updated Jan 12, 2017; https://eu.idtdna.com/pages/education/decoded/article/digital-pcr-(dpcr)-what-is-it-and-why-use-it-

Qian, L., Song, H., & Cai, H. (2016). Determination of Bifidobacterium and Lactobacillus in breast milk of healthy women by digital PCR Benefic. Microbes, 7, 559–569.

Quigley, L., O’Sullivan, O., Beresford, T. P., Ross, R. P., Fitzgerald, G. F., & Cotter, P. D. (2011). Molecular approaches to analyzing the microbial composition of raw milk and raw milk cheeses. International Journal of Food Microbiology, 150, 81–94.

Randazzo, C. L., Torriani, S., Akkermans, A. L. D., de Vos, W. M., & Vaughan, E. E. (2002). Diversity, dynamics, and activity of bacterial communities during production of an artisanal Sicilian cheese as evaluated by 16S rRNA analysis. Applied and Environmental Microbiology, 68, 1882–1892.

Rensen, G. J., Smith, W. L., Jaravata, C. V., Osburn, B., & Cullor, J. S. (2006). Development and evaluation of a real-time FRET probe based multiplex PCR assay for the detection of prohibited meat and bone meal in cattle feed and feed ingredients. Foodborne Pathogens and Disease, 3, 337–346.

Repp, R., Rhiel, S., Heermann, K. H., Schaefer, S., Keller, C., Ndumbe, P., Lambert, F., & Gerlich, W. H. (1993). Genotyping by multiplex polymerase chain reaction for detection of endemic hepatitis B virus transmission. Journal of Clinical Microbiology, 31, 1095–1102.

Reuter, J. A., Spacek, D., & Snyder, M. P. (2015). High-Throughput Sequencing Technologies. Molecular Cell, 58, 586–597.

Rhoads, A., & Au, K. F. (2015). PacBio Sequencing and Its Applications. Genomics, Proteomics & Bioinformatics, 13, 278–289.

Rodríguez-Lázaro, D., & Hernández, M. (2013). Real-time PCR in food science: Introduction. Current Issues in Molecular Biolog, 15, 25–38.

Rudi, K., Rud, I., & Holck, A. (2003). A novel multiplex quantitative DNA array based PCR (MQDA-PCR) for quantification of transgenic maize in food and feed. Nucleic Acid Research, 31, e62 (i-viii).

Rutledge, R. G., & Cote, C. (2003). Mathematics of quantitative kinetic PCR and the application of standard curves. Nucleic Acids Research, 31(16), e93.

Ryley, H. C., Millar-Jones, L., Paull, A., & Weeks, J. (1995). Characterisation of Burkholderia cepacia from cystic fibrosis patients living in Wales by PCR ribotyping. Journal of Medical Microbiology, 43, 436–441.

Sachse K, Frey J (Ed.), Methods in Molecular Biology, PCR Detection of Microbial Pathogens http://drhalim.com/ahri/pcr_detection_of_microbial_pathogens.pdf, 2003, Volume 216, HUMANA PRESS.

Samuels, M., Ellen Prediger, Digital PCR (dPCR)—What is it and why use it?, Jan 12, 2017, Integrated DNA Technologies.

Sandhya, S., Chen, W., & Mulchandani, A. (2008). Molecular beacons: a real-time polymerase chain reaction assay for detecting Escherichia coli from fresh produce and water. Analytica Chimica Acta, 614, 208–212.

Saroj, S. D., Shashidhar, R., Karani, M., & Bandekar, J. R. (2008). Rapid, sensitive, and validated method for detection of Salmonella in food by an enrichment broth culture - nested PCR combination assay. Molecular Cell Probes, 22, 201–206.

Schena, M., Shalon, D., Brown, P., et al. (1995). Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science, 270, 467–470.





































http://drhalim.com/ahri/pcr_detection_of_microbial_pathogens.pdf

http://drhalim.com/ahri/pcr_detection_of_microbial_pathogens.pdf











Schwartz, D. C., & Cantor, C. R. (1984). Separation of yeast chromosome-sized DNAs by pulsed field gradient gel electrophoresis. Cell, 37, 67–75.

Sekse, C., Holst-Jensen, A., Dobrindt, U., et al. (2017). High throughput sequencing for detection of foodborne pathogens. Frontiers in Microbiology, 8, 2029.

Severino, P., Darini, A. L., & Magalhaes, V. D. (1999). The discriminatory power of ribo-PCR compared to conventional ribotyping for epidemiological purposes. APMIS, 107, 1079–1084.

Shalon, D., Smith, S. J., & Brown, P. O. (1996). A DNA microarray system for analyzing complex DNA samples using two-color fluorescent probe hybridization. Genome Research, 6, 639–645.

Sharma, V. K. (2006). Real-time reverse transcription-multiplex PCR for simultaneous and specific detection of rfbE and eae genes of Escherichia coli O157:H7. Molecular Cell Probes, 20, 298–306.

Shreve, M. R., Johnson, S. J., Milla, C. E., Wielinski, C. L., & Regelmann, W. E. (1997). PCR ribotyping and endonuclease subtyping in the epidemiology of Burkholderia cepacia infection. American Journal of Respiratory and Critical Care Medicine, 155, 984–989.

Smith-Vaughan, H. C., Sriprakash, K. S., Mathews, J. D., & Kemp, D. J. (1995). Long PCR- ribotyping of nontypeable Haemophilus influenzae. Journal of Clinical Microbiology, 33, 1192–1195.

Solieri, L., Dakal, T. C., & Giudici, P. (2013). Next-generation sequencing and its potential impact on food microbial genomics. Annals of Microbiology, 63, 21–37.

Song, J. Y., Park, H. G., Jung, S. O., & Park, J. C. (2005). Optical technologies for the read out and quality control of DNA and protein microarrays. Nucleic Acid Research, 33, 1–5.

Southern, E. M. (1975). Detection of specific sequences among DNA fragments separated by gel electrophoresis. Journal of Molecular Biology, 98, 503–517.

Spiro, A., Lowe, M., & Brown, D. (2000). A bead-based method for multiplexed identification and quantitation of DNA sequences using flow cytometry. Applied and Environmental Microbiology, 66, 4258–4265.

Strathdee, F., & Free, A. (2013). Denaturing Gradient Gel Electrophoresis (DGGE). In S. Makovets (Ed.), DNA Electrophoresis. Methods in Molecular Biology (Methods and Protocols). Totowa, NJ: Humana Press vol 1054.

Szabo, E. A., & Mackey, B. M. (1999). Detection of Salmonella enteritidis by reverse transcription-polymerase chain reaction (PCR). International Journal of Food Microbiology, 5, 113–122.

Tengs, T., Kristoffersen, A. B., Berdal, K. G., Thorstensen, T., Butenko, M. A., Nesvold, H., & Holst Jensen, A. (2007). Microarray based method for detection of unknown genetic modifications. BMC Biotechnology, 7, 91 (1-8).

Trapmann, S., & Emons, H. (2005). Reliable GMO analysis. Analytical and Bioanalytical Chemistry. 2005, 381, 72–74.

Tsiatis, A. C., Norris-Kirb, y A., et al. (2010). Comparison of Sanger sequencing, pyrosequencing, and melting curve analysis for the detection of KRAS mutations: diagnostic and clinical implications. Journal of Molecular Diagnostics, 12, 425–432.

Tyagi, S., & Kramer, F. R. (1996). Molecular beacons: Probes that fluoresce upon hybridization. Nature Biotechnology, 14, 303–308.

Tyagi, S., Bratu, D. P., & Kramer, F. R. (1998). Multicolor molecular beacons for allele discrimination. Nature Biotechnology, 16, 49–53.

U.S. FDA, Examples of How FDA Has Used Whole Genome Sequencing of Foodborne Pathogens For Regulatory Purposes, 2018, https://www.fda.gov/Food/FoodScienceResearch/WholeGenomeSequencingProgramWGS/ucm422075.htm.
























































Vardaka, E., Kormas, K.A., Katsiapi, M., Genitsaris, S., Moustaka-Gouni, M., 2016. Molecular diversity of bacteria in commercially available “Spirulina” food supplements. Esteban MÁ, ed. PeerJ. 4:e1610.

Vega, E. D., & Marina, M. L. (2014). Characterization and study of transgenic cultivars by capillary and microchip electrophoresis. International Journal of Molecular Sciences, 15(12), 23851–23877.

von Götz, F. (2010). See what you eat--broad GMO screening with microarrays. Analytical and Bioanalytical Chemistry. 2010, 396(6), 1961–1967.

Vos, P., Hogers, R., Bleeker, M., Reijans, M., van de Lee, T., Hornes, M., Frijters, A., Pot, J., Peleman, J., & Kuiper, M. (1995). AFLP: a new technique for DNA fingerprinting. Nucleic Acids Research, 23, 4407–4414.

Waiblinger, H. U., Ernst, B., Anderson, A., & Pietsch, K. (2008). Validation and collaborative study of a P35S and T-nos duplex real-time PCR screening method to detect genetically modified organisms in food products. European Food Research and Technology, 226, 1221–1228.

Wang, D. G., Fan, J. B., Siao, C. J., Berno, A., Young, P., Sapolsky, R., Ghandour, G., Perkins, N., Winchester, E., Spencer, J., et al. (1998). Large-scale identification, mapping, and genotyping of single-nucleotide polymorphisms in the human genome. Science, 280, 1077–1082.

Wang, D., Wu, Q., Yao, L., Wei, M., Kou, X., & Zhang, J. (2008). New target tissue for food-borne virus detection in oysters. Letters in Applied Microbiology, 47, 405–409.

Wassenaar, T. M., & Newell, D. G. (2000). Genotyping of Campylobacter spp. Applied and Environmental Microbiology, 66(1), 1–9.

Way, J. S., Josephson, K. L., Pillai, S. D., Abbaszadegan, M., Gerba, C. P., & Pepper, I. L. (1993). Specific detection of Salmonella spp. by multiplex polymerase chain reaction. Applied and Environmental Microbiology, 59, 1473–1479.

Whale, A. S., Huggett, J. F., et al. (2012). Comparison of microfluidic digital PCR and conventional quantitative PCR for measuring copy number variation. Nucleic Acids Research, 40(11), e82.

Whitcombe D. Scorpion Primers and probes. http://www.premierbiosoft.com/ tech_notes/ Scorpion.html. (December 2011).,

Whiteley, N. M., Hunkapiller, M.W., Glazer, A. N. (1989). Detection of specific sequences in nucleic acids. U.S. patent no. 4,883,750.

Wiedmann, M., Barany, F., & Bart, C. A. (1993). Detection of Listeria monocytogenes with a nonisotopic polymerase chain reaction-coupled ligase chain reaction assay. Applied and Environmental Microbiology, 59, 2743–2745.

Willems, S., Fraiture, M., Deforce, D., et al. (2016). Statistical framework for detection of genetically modified organisms based on Next Generation Sequencing. Food Chemistry, 192, 788–798.

Wilmes, P., Simmons, S. L., Denef, V. J., & Banfield, J. F. (2009). The dynamic genetic repertoire of microbial communities. FEMS Microbiology Review, 33, 109–132.

Wilton, S., & Cousins, D. (1992). Detection and identification of multiple mycobacterial pathogens by DNA amplification in a single tube. PCR Methods Applications, 1, 269–273.

Winn-Deen, E. S., & lovannisci, D. M. (1991). Sensitive fluorescence method for detecting DNA ligation amplification products. Clinical Chemistry, 37, 1522–1523.

Winnicka, A., Sawosz, E., Klucinski, W., Kosieradzka, I., Szopa, J., Malepszy, S., & Pastuszewska (2001). A note on the effect of feeding genetically modified potatoes on selected indices of nonspecific resistance in rats. Journal of Animal and Feed Sciences, 10, 13–18.

Woese, C. R. (1987). Bacterial evolution. Microbiological Review, 51, 221–271.




























http://www.premierbiosoft.com






















Woese, C. R. (1996). The world of ribosomal RNA. In R. A. Zimmermann, & A. E. Dahlberg (Eds.), Ribosomal RNA: Structure, evolution, processing, and function in protein biosynthesis (pp. 23–48). Boca Raton, FL.: CRC Press.

Wu, D. Y., & Wallace, R. B. (1989). The ligation amplification reaction (LAR)-Amplification of specific DNA sequences using sequential rounds of template dependent ligation. Genomics, 4, 560–569.

Yamamoto, Y. (2002). PCR in diagnosis of infection: detection of bacteria in cerebrospinal fluids. Clinical and Diagnostic Laboratory Immunology, 9(3), 508–514.

Yoda, T., Suzuki, Y., Yamazaki, K., Sakon, N., Aoyama, I., & Tsukamoto, T. (2007). Evaluation and application of reverse transcription loop-mediated isothermal amplification for detection of noroviruses. Journal of Medical Virology, 79, 326–334.

You, Y., Fu, C., Zeng, X., Fang, D., Yan, X., Sun, B., Xiao, D., & Zhang, J. (2008). A novel DNA microarray for rapid diagnosis of enteropathogenic bacteria in stool specimens of patients with diarrhea. Journal of Microbiological Methods, 75, 566–571.

Zazzi, M., Romano, L., Brasini, A., & Valensin, P. E. (1993). Simultaneous amplification of multiple HIV-1 DNA sequences from clinical specimens by using nested-prime polymerase chain reaction. AIDS Research and Human Retroviruses, 9, 315–320.

Zebala, J. A., & Barany, F. (1993). Detection of Leber’s hereditary optic neuropathy by nonradioactive LCR. In D. H. Gelfand, J. J. Sninsky, & M. A. Innis (Eds.), In PCR strategies. San Diego, CA: Academic Press.

Zhou, S., Hou, Z., Li, N., & Qin, Q. (2007). Development of a SYBR Green I real-time PCR for quantitative detection of Vibrio alginolyticus in seawater and seafood. Journal of Applied Microbiology, 103, 1897–1906.

Zhuo, Q., Chen, X., Piao, J., Gu, L., Sheng, W., & Jiu, Y. (2004). Study on food safety of genetically modified rice which expressed cowpea trypsin inhibitor by 90 day feeding test on rats. Journal of Hygiene Research, 33, 176–179.































5 - recent trends in molecular techniques for food

Documents