qpcr as a powerful tool for microbial food spoilage quantification: significance for food quality

Trends in Food Science & Technology 22 (2011) 367e376

Review

* Corresponding author.

0924-2244/$ - see front matter � 2011 Elsevier Ltd. All rights reserved.doi:10.1016/j.tifs.2011.04.004

qPCR as a powerful

tool for microbial

food spoilage

quantification:

Significance for food

quality

Noelia Mart�ınez,
Maria Cruz Mart�ın,
Ana Herrero,Mar�ıa Fern�andez,

Miguel A. Alvarez* andVictor Ladero

Instituto de Productos L�acteos de Asturias,

(IPLA-CSIC), 33300 Villaviciosa, Asturias, Spain

(Tel.: D34 985 89 21 31; fax: D34 985 89 22 33;

e-mails: [email protected]; [email protected];

[email protected]; [email protected];

[email protected]; [email protected])

The use of real time quantitative PCR (qPCR) has recently been

extended to food science. The literature has mainly focused on

its use in ensuring food safety. However, it offers a number of

advantages with respect to the quantification of non-

pathogenic food spoilage microorganisms. Indeed, qPCR

may have a promising future in improving the quality of

food products. The present review examines the use of qPCR

in this area, the basis of the technique, the requirements that

must be met for optimal qPCR assays to be performed, and

the advantages it offers over other techniques.

IntroductionReal time quantitative PCR (qPCR) has recently entered

service in the field of food science and technology. Therapid development of this technique is reflected in the in-creasing number of research articles and patents to be foundin databases when ‘qPCR’ and ‘food’ are used as searchkeywords. Indeed, qPCR is now employed in the manage-ment of nearly all food safety and quality problems. Oneof the best developed and successful applications ofqPCR is the detection and quantification of pathogens, in-cluding viruses, bacteria and eukaryotic microorganisms,as well as a number of parasites (Levin, 2004). Severalmethods have also been developed for the detection andquantification of opportunistic pathogens in food products(Querol & Fleet, 2006, chap. 12; Makino, Fujimoto, &Watanabe, 2010). It has also been used to monitor the pres-ence of antibiotic resistance genes that might be transferredto pathogenic or commensal bacteria in cheese and otherfood-related scenarios (Manuzon et al., 2007). New appli-cations include the detection of food ingredients (Tanabeet al., 2007) and ingredient fraud (Mafra, Ferreira,Beatriz, & Oliveira, 2008), and the monitoring of unin-tended contamination of special foods (e.g., gluten-freefoods) (Sandberg, Lundberg, Ferm, & Yman, 2003). Itmay also be used to study toxin-encoding genes (Fischeret al., 2007), to detect genetically modified organisms(Rodr�ıguez-L�azaro et al., 2007), allergens (K€oppel et al.,2010), and certain non-pathogenic spoilage microorgan-isms (NPSMs). Although the literature currently containslittle on qPCR for the detection of NPSMs, research inthis area is progressing and the use of the technique islikely to gain importance in the future.

NPSMs have different origins, but in general they arepresent at low concentration in the raw materials used orcontaminate the food during its processing. Their numbersmay grow during both processing and storage (Huis in’tVeld, 1996); it is generally recognized that the total absenceof NPSMs is an unreachable goal. NPSMs have an impor-tant negative impact on food quality and therefore on theireconomic value. In some cases they can even have an im-pact on food safety. Their rapid identification is thereforeof great importance to the food industry; early detectionand quantification might allow appropriate actions be takento avoid their negative impacts.

This review describes the basis of qPCR assays, the dif-ferent markers that can be used in them, and the advantages

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http://dx.doi.org/10.1016/j.tifs.2011.04.004






368 N. Mart�ınez et al. / Trends in Food Science & Technology 22 (2011) 367e376

of this technique over other microbiological and molecularmethods. The requirements and challenges of qPCR quan-titative detection of NPSMs are also analysed. Finally, a de-scription of the qPCR assays currently available isprovided, with special attention paid to those already onthe market.

The basis and chemistry of qPCRCulture-independent molecular methods have become

recognised as powerful and reliable tools for use in ensuringfood quality and safety. From PCR to DNA-arrays, a widerange of methods has been developed for use in the detectionof foodborne microorganisms (for a review see Lauri &Mariani, 2009). However, the quantification of microbialpopulations in food matrices by molecular methods is be-coming even more necessary, especially with respect to cer-tain spoilage microorganisms. In this respect, qPCRrepresents a powerful tool that could greatly help guaranteethe safety and quality of foodstuffs. qPCR allows the prog-ress of the PCR reaction to be monitored as it occurs inreal time. Data are collected throughout the reaction, notjust at the end point, and reactions are characterized by thecycle in which the amplification of a target DNA is detectedrather than the amount of DNA product accumulated at theend. Such monitoring of the reaction has been made possibleby the development of methods to fluorescently label theDNA synthesized in each cycle, and the measurement ofthis DNA by fluorescence detectors incorporated into ther-mocyclers. The cycle in which the fluorescence reaches thedetection level of the instrument is known as the thresholdcycle (Ct) and it is directly proportional to the initial copiesof target DNA over a wide dynamic range (Logan, Edwards,& Saunders, 2009).

The detection methods used in qPCR can be classifiedinto two main groups: (i) non-specific methods that detectall double stranded DNA (dsDNA) produced in the reac-tion, and (ii) amplicon sequence-specific methods that dis-tinguish target sequence amplifications from primer-dimersor non-specific amplifications.

The simplest andmost used type of qPCR is based on non-specific quantification methods that involve DNA-bindingfluorophores such as ethidium bromide, YO-PRO-I, SYBRgreen I, SYBR Gold, BEBO, BOXTO, LCGreen andSYTO9. These molecules are DNA minor-groove bindersthat emit a strong fluorescent signal only when associatedwith dsDNA and exposed to the appropriate wavelength oflight. The use of these compounds requires no additional ol-igonucleotide design nor chemical conjugation, and they areminimally affected by small changes in the template se-quence (Logan et al., 2009). However, the formation ofprimer-dimers is common and strongly associated with theentry of the reaction into its plateau phase. The formationof these primer-dimers and other non-specific amplificationproducts can hinder the interpretation of the results. Theseproblems can be partially solved using software, analysingthemelting curve of the amplifiedDNA. If the qPCR reaction

is fully optimised, a melting peak profile that represents thespecific product can be produced. Based on the results ofsuch analysis, non-specific fluorophores can also be usedfor the identification of microorganisms.

Fluorescent probes are used in methods to detect specificsequences. Their use adds an additional level of specificityto the amplification reaction. Different types of probe havebeen developed. Most of them are based on double-dye ol-igonucleotides that emit a signal only after hybridisation tothe target DNA has occurred (molecular beacons, MGBEclipse, Scorpions), or after their degradation by the 50-30

exonuclease activity of DNA polymerase during the ampli-fication process (TaqMan oligoprobe, TaqMan-MGB). Anumber of less commonly used probes are also available,e.g., universal template primer [UT], the Padlock probe,Qzyme, Resonsense light-up probes and Hy-Beacon probes(Logan et al., 2009).

Most qPCR applications are designed to detect DNA tar-gets, although the detection of RNA molecules is also possi-ble. Since the turnover of RNA is rapid, its detection isusually associated with viable or at least metabolically activemicroorganisms. Two techniques are mainly used in thequantification of RNA: reverse transcription qPCR (RT-qPCR) and real time nucleic acid sequence-based amplifica-tion (RT-NASBA). In RT-qPCR a first step of retrotranscrip-tion is performed to synthesize cDNA, which is then used asa template in a standard qPCR amplification. RT-NASBA isan isothermal nucleic acid amplification method usually per-formed at 41 �C with steps involving the use of reverse tran-scriptase, RNA polymerase and RNAse H, followed by RNAquantification (Logan et al., 2009).

Requirements for accurate qPCR assaysAccuracy is of great importance in microbiological anal-

yses of NPSMs. Reliable quantification depends on opti-mised and carefully performed qPCR reactions. Theaccuracy of qPCR is influenced by primer design, the qual-ity of the template DNA, the presence of inhibitors(Edwards & Logan, 2009), and the handling and storageof samples, primers, probes and enzymes (Dionisi et al.,2003). With food samples, special attention must be paidto the possible presence of inhibitors, and to the efficiencyof DNA extraction. A thorough microbiological knowledgeof the food in question, including its usual microbiota andpotential contaminants, is also a prerequisite.

Once the microorganisms to be detected have been de-cided upon, a target gene must be selected and specificprimers to recognise it must be designed. The selection ofthe target gene is of great importance. Targeting a genehighly conserved among different species can be used inbroad-based detection strategies, while targeting a DNA se-quence unique to a particular species or even strain can pro-vide a highly specific test (Hanna, Connor, & Wang, 2005).The best option when searching for spoilage organisms is toselect a functional gene related to the spoilage effect. How-ever, this is not always possible due to a lack of detailed

369N. Mart�ınez et al. / Trends in Food Science & Technology 22 (2011) 367e376

genetic information. In such cases, the 16S rRNA sequencecan be used to design specific primers and probes. How-ever, it should be remembered that quantification is affectedby the copy numbers of the 16S rRNA genes present. Theirdesign should take into account that closely related organ-isms often share DNA sequences in the most conserved re-gion, whereas species of the same genus may bedistinguished by different DNA sequences in the variableregions (Woese, Kandler, & Wheelis, 1990).

Probes, primers, and PCR conditions should be opti-mised not just for a low detection limit (sensitivity) butalso for a broad dynamic range (efficiency). The optimalconcentration of each of the oligonucleotides used in the as-say should also be optimised. The amount of DNA poly-merase added is important as well: too little could lead toinefficient amplification and a loss of sensitivity (Edwards& Logan, 2009).

The results of qPCR analysis may be affected by PCR in-hibitors present in food samples. Ideally, each sample shouldbe serially diluted and tested in duplicate PCR runs to deter-mine whether any inhibitors are present. However, the bestalternative to this is the incorporation of an internal control(Levin, 2004). This should allow the presence of amplifica-tion inhibitors to be detected and is very useful in the identi-fication of false negative results. In addition, internal controlscan be used to detect the effect of the food matrix on the ef-ficiency of qPCR assays. This is done by spiking the food tobe analysed and performing the assay with serial dilutions ofthis food (Schneider, Enkerli, & Widmer, 2009).

In order to perform a reliable quantification, the properuse of standards is also needed. Total DNA of the microor-ganism to be detected, the target gene or the target genecloned in a plasmid can be used as standard, but it is thelast option the most recommendable for easiness of produc-tion and stability. In any case, the precise quantification ofthe DNA used as standard is essential. Once made, stan-dards are typically used for extended periods of time andtheir stability is therefore a critical, but frequently ignoredissue (Dhanasekaran, Doherty, & Kenneth, 2010). The mostsuitable alternative for commercial purposes is the develop-ment of ready to use plates that include all the necessarystandards and chemicals lyophilized.

qPCR compared with other detection methodsThe introduction of strict food safety regulations made

the availability of methods capable of reliably quantifyingfood contaminants essential. Such methods must not onlyto detect contaminating microorganisms, but to preventeconomic losses due to false positives.

qPCR is fast, allows for quantitative analysis and re-quires no post-processing. In addition, it is economicallyviable, results are obtained quickly, and the number of mi-croorganisms and the level to which they can be identified(genus, species or serotype) is expanding. The more tradi-tional methods have many disadvantages compared toqPCR. For example, those based on the isolation and

phenotypic characterization can be expensive and takedays to complete (Fig. 1). Culture-based methods are labo-rious and a number of incubation conditions, such as an ad-equate temperature and an aerobic or anaerobicatmosphere, must normally be provided (Gammon et al.,2007). Further, tests based on selective culture media oftenfail to detect certain strains within the target population, re-sulting in the underestimation of numbers (Just�e, Thomma,& Lievens, 2008). Moreover, since conventional methodsare not able to detect non-cultivatable cells, stressed orweakened cells may need specific culture conditions to firstrecover before any quantification is possible. Even in foodmatrices, where cultivatable microorganisms are predomi-nant, some 25e50% of the active microbial communitymay not be cultivatable (Just�e et al., 2008). An alternativeis the use of immunoassays to detect molecules such assugar moieties or proteins, but these require the raising ofspecific antibodies and are not well suited to the detectionof unwanted food ingredients in highly processed food, no-tably because proteins are less thermostable than DNA(Gachon, Mingam, & Charrier, 2004).

Despite the high sensitivity of qPCR methods, the con-centration of spoilage microorganisms in food samples issometimes below the detection limit. Previous enrichmentculture is therefore commonly necessary, especially if onehas to be absolutely sure that a microorganism is absent(Hanna et al., 2005). Nonetheless, enrichment times forqPCR are shorter than with other methods due to the tech-nique’s higher sensitivity (Mart�ın et al., 2010) (Fig. 1). Tra-ditional culture methods need between 2 or 3 days to detectmicroorganism that require a previous enrichment step,while qPCR may need less than 12 h (Mart�ın et al.,2010). However, it is important to note that when anypre-enrichment step is carried out, the possibility of quan-tification is diminished or even impossible.

Another advantage of qPCR is that it can be used to in-directly measure the concentration of undesirable or eventoxic compounds produced by spoilage microorganisms,such as biogenic amines (BAs). In some foods, the presenceof BAs indicates that hygiene during manufacture has beenpoor. BAs accumulate in food by the microbial decarboxyl-ation of certain amino acids, and they can reach concentra-tions hazardous to health (Taylor, 1985). The quantificationof BAs has traditionally been performed in final products,and using analytical methods that are often long andtedious. The capacity to detect BA-producing bacteriaearly, and to be able to check large numbers of samplesin a short time, would, therefore, be of great advantage tothe food industry. In addition, it would allow appropriateinterventions be undertaken, before the BA concentrationreaches unhealthy levels. Although microbiological screen-ing methods based on media containing a pH indicator andconventional PCR methods have been proposed (Marcobal,de las Rivas, & Mu~noz, 2006), none of them relate the pres-ence of BA-producing microorganisms to the final BA con-tent. However, a direct relationship has been established

Fig. 1. Comparison of conventional microbiological and qPCR methods for the quantification of eight spoilage microorganism in 10 food samples.The approximate time (six days vs. two days) and materials required (320 plates vs. 1 qPCR plate) for each type of analysis are indicated.


between qPCR results for BA-producers and the BA con-centration of food samples (Ladero, Linares, Fern�andez,& Alvarez, 2008; Ladero, Mart�ınez, Mart�ın, Fern�andez,& Alvarez, 2010). Indeed, a number of qPCR tests areavailable for use with different types of food matrix(Landete, de las Rivas, Marcobal, & Mu~noz, 2011). More-over, a threshold Ct has been established that allows theclassification of samples as potentially dangerous(Ladero, Mart�ınez et al., 2010).

qPCR for the quantitative detection of food spoilagemicroorganisms

Many studies have confirmed the value of qPCR asa rapid and reliable routine method that could be used infood manufacturing plants for detecting fastidious organ-isms (Table 1).

Spoilage microorganisms have been divided into broadcategories based on certain phenotypic characteristics, butonly in few cases are these related to the spoilage problemsthey cause. These groups include yeasts and moulds,Gram-negative rod shaped bacteria (e.g., Pseudomonas,Aeromonas, Vibrio), Gram-positive spore forming bacteria(e.g., Bacillus and Clostridium spp.), lactic acid bacteria(e.g., Lactobacillus, Streptococcus, Leuconostoc, and Pedio-coccus spp.), other Gram-positive bacteria (e.g., Brochotristhermospizucta, Micrococcus spp.), and bacteriophages.qPCR has been proposed as a means of detecting some ofthese groups (see Table 1), such as yeasts and moulds(Casey & Dobson, 2004), not only those considered as spoil-age microorganisms but some genera described as opportu-nistic pathogens. It can also be used to detect total viablebacteria (Lee & Levin, 2007), members of the phylum

Firmicutes (Haakensen, Dobson, Deneer, & Ziola, 2008),thermophilic bacilli (Rueckert, Ronimus, & Morgan,2006), strictly anaerobic bacteria of the class Clostridia(Juvonen, Koivula, & Haikara, 2008), lactic acid bacteria(Haakensen, Butt, Chaban, Deneer, & Ziola, 2007), Pseudo-monas (Reynisson, Lauzon, Magnusson, Hreggvidsson, &Marteinsson, 2008), Gram-negative histamine producers infish products (Bjornsdottir-Butler, Jones, Benner, &Burkhardt, 2011), tyramine-producing strains (Ladero,Fern�andez, Cuesta, & Alvarez, 2010) and bacteriophagesof LAB involved in the spoilage of fermented dairy products(Mart�ın, del Rio, Mart�ınez, Magad�an, & Alvarez, 2008;del Rio, Mart�ın, Mart�ınez, Magad�an, & Alvarez, 2006;del Rio, Mart�ın, Mart�ınez, Magad�an, & Alvarez, 2008).

Several methods based on qPCR are also available forquantifying a number of bioindicators used to assess hy-giene levels during food manufacture. Bioindicators are mi-croorganisms, or groups of microorganisms, whosepresence in given numbers indicates inadequate hygieneand the possible presence of pathogens (Mossel, Corry,Struijk, & Baird, 1995). In general, they are mainly usedto assess food and drink quality (Jay, 2001). Among theseindicators are faecal bacteria, such as coliforms, Bifidobac-teria, enterococci, or coliphages/enteroviruses. These areeasily detected and can be used as markers of pathogenic,enteric or zoonotic agents (Jay, 2001). Pseudomonas isa psychotropic bacterium particularly involved in the spoil-age of food stored at low temperatures, and is frequentlyused as an indicator (Jay, Vilai, & Hughes, 2003).

The ability to test for specific spoilage microorganisms(SSOs) (Huis in’t Veld, 1996) is becoming increasing pos-sible. Several qPCR assays (Table 1) have been developed

Table 1. Non-exhaustive list of qPCR assays described in the literature for the detection and quantification of NPSMs in food matrices. The genetarget and fluorescent markers employed are indicated.

Microorganism gene target qPCR fluorescentmarkers

Food Reference

Yeasts and mouldsGeneralYeasts and Moulds CS1 SYBR Green Fruit juice Casey & Dobson, 2004Yeasts 5.8S-ITS SYBR Green Orange juice Renard, G�omez di Marco,

Egea-Cortines, & Weiss, 2008Yeast (as opportunisticpathogens)

26S rRNA SYBR Green Dairy products Makino et al., 2010

Moulds 18S rRNA TaqMan probe Orange juice Wan et al., 2006

SSOSaccharomyces cerevisiae RAPD-fragment SYBR Green Wine Martorell et al., 2005Brettanomyces 18S rRNA TaqMan probe Orange juice Wan et al., 2006Hanseniaspora sp. D1/D2 26S

rRNASYBR Green Wine/Juice Phister, Rawsthorne, Joseph, &

Mills, 2007Zygosaccharomyces bailli 26S rRNA SYBR Green Wine and

Fruit juicesRawsthorne & Phister, 2006

Dekkera bruxellensis 26S rRNA SYBR Green Wine Phister & Mills, 2003

BacteriaGeneralTotal viable bacteria 16S rRNA SYBR Green Refrigerated fish Lee & Levin, 2007Firmicutes Phylum 16S rRNA TaqMan probe Beer Haakensen et al., 2008Strictly anaerobic bacteria(class Clostridia)

16S rRNA SYBR Green Beer Juvonen et al., 2008

Acetic acid bacteria 16S rRNA SYBR Green Wine Gonz�alez, Hierro, Poblet, Mas, &Guillam�on, 2006

Lactic acid bacteria horA TaqMan probe Beer Haakensen et al., 2007Thermophilic bacilli spo0A SYBR Green Milk powder Rueckert et al., 2006Enterobacteriaceae LacZ SYBR Green Dairy products Mart�ın et al., 2010

SSOBrochothrix thermosphacta 16S rRNA SYBR Green Raw meat Pennacchia et al., 2009Lactobacillus sakei 16-23 ITS TaqMan probe Meat/fermented

sausagesMart�ın et al., 2006

Pseudomonas carA SYBR Green Fish Reynisson et al., 2008Brettanomyces bruxellensis Rad4 SYBR Green Wine Delaherche et al., 2004Pediococcus damnosus ropystrains

dps SYBR Green Wine Delaherche et al., 2004

Xylella fastidiosa 16-23S ITS TaqMan probe Wine Schaad et al., 2002Obesumbacterium proteus 16S rRNA SYBR Green Beer Koivula, Juvonen, Haikara, & Suihko,

2006Alicyclobacillus spp. 16S rRNA TaqMan probe Juice products Connor, Luo, Gardener, & Wang, 2005GluconobacterGluconacetobacter

16S rRNA TaqMan probe Electrolytereplacement drink

Gammon et al., 2007

Escherichia coli clpB Molecular BeaconNASBA

water Heijnen & Medema, 2009

Bacillus spp. hblC Molecular BeaconNASBA

Milk Gore, Wakeman, Hull, & McKillip, 2003

Clostridium tyrobutyricum fla TaqMan probe Milk L�opez-Enr�ıquez et al., 2007Lactococcus lactis subspcremoris

16S rRNA SYBR Green Milk fermented Grattepanche, Lacroix, Audet, &Lapointe, 2005

Enterococcus gilvus pheS TaqMan probe Cheese Zago, Bonvini, Carminati, &Giraffa, 2009

VirusesEnteric viruses NV TaqMan probe Berries and

vegetablesButot, Putallaz, & S�anchez, 2007

FRNA bacteriophages NoV TaqMan probe Oysters Flannery, Keaveney, & Dor�e, 2009Lactobacillus delbrueckii mur/lysA TaqMan probe Milk Mart�ın et al., 2008Streptococcus thermophilus orf1510/orf18 TaqMan probe Milk del Rio et al., 2008

GramD biogenic amine producersHistamine hdcA SYBR Green Dairy products Fern�andez et al., 2006

(continued on next page)


Table 1 (continued)

Microorganism gene target qPCR fluorescentmarkers

Food Reference

Putrescine odc/agdi SYBR Green Wine Nannelli et al., 2008Tyramine tdc SYBR Green Meat Torriani et al., 2008

GramL biogenic amine producersHistamine hdc TaqMan probe Fish Bjornsdottir-Butler et al., 2011

ITS: Internal transcribed spacer region including the 5.8 rRNA gene. RAPD: Random amplification polymorphic DNA.


for the identification of SSOs in different food matrices,such as Clostridium tyrobutyricum (L�opez-Enr�ıquez,Rodr�ıguez-L�azaro, & Hern�andez, 2007), Pediococcusdamnosus ropy strains (Delaherche, Claisse, & Lonvaud-Funel, 2004), and Sacharamyces cerevisiae (Martorell,Querol, & Fern�andez-Espinar, 2005).

Other qPCR assays have been developed to monitor thegrowth of microorganisms with a major role in the produc-tion of fermented foods and beverages, such as LAB indairy or meat fermentation (Mart�ın, Jofr�e, Garriga, Pla, &Aymerich, 2006), and yeast in the manufacture of fer-mented alcoholic beverages (Martorell et al., 2005). Never-theless, these assays can also be used in situations in whichthese microorganisms are undesirable, for example thepresence of yeast in many foods or elevated concentrationsof LAB in certain drinks (Jespersen & Jakobsen, 1996). Insome cases, a fine line separates spoilage from beneficialactivity. The decarboxylation of di- and tricarboxylic acidsby LAB is a desirable step resulting in the production ofcompounds that enhance the organoleptic properties and/or the stability of finished fermented products (vanKranenburg et al., 2002). However, the decarboxylationof amino acids (e.g., histidine, tyrosine) leads to the pro-duction of BAs. There are now several qPCR assays thatcan detect and quantify LAB strains that produce BAs indifferent food matrices (Fern�andez, del R�ıo, Linares,Mart�ın, & Alvarez, 2006; Ladero, Fern�andez et al., 2010;Ladero, Mart�ınez et al., 2010; Nannelli et al., 2008;Torriani et al., 2008), as well as for the detection ofhistamine-producing gram-negative bacteria belonging todifferent genera (Bjornsdottir-Butler et al., 2011) (Table 1).

The detection of foodborne bacteria carrying antibioticresistance genes is of increasing interest. There is growingevidence that the use of antibiotics in stock raising is leadingto human pathogens developing resistance to them (Wan,Yousef, Schwartz, & Wang, 2006). Commensal bacteria,and the antibiotic resistance (AR) genes they harbour, can en-ter the human food chain through meat or milk products, orvia foods grown in fields fertilized with animal manure orwastewater. Due to their enormous abundance, commensalbacteria can serve as a reservoir of AR genes and probablycontribute to AR gene transfer among bacteria, includingpathogenic bacteria (Johnston & Jaykus, 2004). qPCR hasbeen used tomonitor antimicrobial resistance in food and en-vironmental scenarios (Manuzon et al., 2007).

qPCR has also been used for the detection of opportunisticpathogens in foodstuffs (Querol & Fleet, 2006, chap. 12;Makino et al., 2010). Finally, qPCR has also been proposedfor the detection of certain plant pathogens affecting cropmar-ketability, e.g.,Fusarium graminearum in cereal grains (Dyer,Kendra, & Brown, 2006), Candidatus liberibacter solanacea-rum in potato and tomato (Li et al., 2009), or Cucumber veinyellowing virus in plants (Pic�o, Sifres, & Nuez, 2005).

Commercial qPCR kits for the detection of foodspoilage microorganisms

The qPCR has proven to be a very powerful tool to de-tect pathogens (Levin, 2004). In addition, it offers many ad-vantages in the detection of microorganisms of interest tothe food industry - particularly in the monitoring of startercultures for fermented foods (of great importance if highquality and safe final products are to be obtained) and inthe quantification of probiotics in functional foods and bev-erages (Collado, Delgado, Maldonado, & Rodr�ıguez, 2009;Pennacchia, Ercolini, & Villani, 2009). Despite these ad-vantages, there are still reservations about its routine usein food analysis. Certainly, its full introduction into thefood industry will require the availability of adequatelytrained staff, the adaptation of the protocols described inthe scientific literature to the everyday practice of analyticallaboratories, and the availability of reagents in the form ofkits at a reasonable price (particularly if qPCR is to be usedby laboratories processing small numbers of samples).

To date, several commercial kits have been developedfor the detection of the main foodborne pathogens. How-ever, only a few have been produced for the determinationof spoilage food microorganisms (Table 2) - although theyare available for use in research laboratories (Fern�andezet al., 2006; Mart�ınez-Blanch, S�anchez, Garay, & Aznar,2009). Many oligonucleotides have also been designedfor the identification of these kinds of microorganism, butfew have been marketed (Table 1). Certainly, only a fewcommercial kits for the detection of NPSMs are available.Some of these allow the general detection of non-specificmicroorganisms in all kind of foods, e.g., the SystemBAX� (DuPont Qualicon, Wilmington, Delaware) kit forthe detection of yeasts and moulds. The further develop-ment of kits for the routine detection of NPSMs could im-prove food production via the implementation of hazardanalysis and critical control point (HACCP) systems.

Table 2. qPCR commercial kits available for the detection and quantification of NPSMs in foods.

Kit name Target species Food matrix Sensitivity (cfu mlL1) Manufacturer

System Bax associated Yeasts and moulds Prepared foods c 104 DuPont Qualicon

Foodproof Detection System Enterobacteriaceae Prepared foods c 101e103 Merck

Foodproof� Beer Screening kit Lactobacillus Beer c 101e103 MerckMegasphaeraPectinatusPediococcus

Primermix P1 Screening Acetobacter Beer 2 � 101e1 � 102 Gen-ialLactobacillusMegasphaeraPectinatusPediococcusSelenomonas


The Foodproof� Detection System for Enterobacteria-ceae (Merck, Darmstadt, Germany) is another importantkit; the presence of Enterobacteria indicates poor hygienepractices in food manufacture. Some kits allow the detec-tion of SSOs in certain foods. For example, the PrimermixP1 Screening (Gen-ial, Troisdorf, Germany) andFoodproof� Beer Screening kit (Merck, Darmstadt, Ger-many) detects more than 25 spoilage organisms identifiedas contaminants of beer. The latter Foodproof� kit, devel-oped and validated in cooperation with a number of largeGerman breweries, has a sample processing time of just30 min to 1 h, and an enrichment time of up to 18 h. TheqPCR procedure itself takes about 2 h. Thus, the time toobtain results is shorter by several days compared tostandard microbiological and biochemical methods.

Our group has developed and implemented two qPCRassays to detect Streptococcus thermophilus and Lactobacil-lus bulgaricus phages (del R�ıo et al., 2008; 2006 respec-tively), in a dairy company although they have not beenmarketed. Bacteriophage infection of dairy starters is a ma-jor cause of milk fermentation failure (Neve & Teuber,1991). A reliable system for their early detection in milkis vital given the magnitude of the problems they causeand their associated economic impact. A phage populationof over 105 pfu ml�1 poses a serious risk of fermentationfailure (Neve & Teuber, 1991); such numbers are, however,within the detection limits of qPCR. Multiplex qPCR is per-formed with an internal amplification control that uses spe-cific primers and TaqMan-MGB probes for two differentgenes. In addition to the quantitative detection of phages,this allows the identification of cos and pac type S. thermo-philus phages (del R�ıo, et al., 2008). This method has beenoptimised for FAST technology (Applied Biosystems, Cal-ifornia, USA), which reduces the assay time without loss ofsensitivity. Thus, bacteriophages in milk samples can be de-tected, quantified and typified in about 30 min. The rapid,accurate identification of bacteriophages potentially ableto attack starter cultures allows decisions concerning thefinal use of milk thus contaminated to be quickly taken.Such milk might be earmarked for use in processes in

which phages are deactivated, processes that do not requirestarters, or processes that employ starter bacteria insensitiveto the detected phage.

Challenges and future of qPCR in the quantitativedetection of food spoilage microorganisms

Most of the technical challenges encountered in usingqPCR with food matrices have been overcome (Hannaet al., 2005; Levin, 2004). However, compared to its usein clinical testing, qPCR for the detection of spoilage mi-croorganisms is still in early days. The main challenge isthe many types of food that need to be tested, and thefact that many contain PCR inhibitors. The presence ofinhibitors should be carefully checked for to ensure theaccurate quantification of the target microorganisms (seeRequirements for accurate qPCR assays).

Ideally, food samples should be used directly as templateproviders. However, nucleic acids are sometimes betterextracted from the food matrix. It should always be bornein mind, however, the quantification of a pathogen canvary by up to two log units depending of the lysis methodused (Cheng & Griffiths, 2003). Extraction methods facetwo main challenges. The first is posed by heterogeneityof the matrix in terms of its physical state (liquid or solid),texture, and composition (concentrations of proteins, sugarsor fat), etc (a single extraction method valid for all foodsand beverages is hard to come by). Independent of the ma-trix to be analysed, the nucleic acid extraction method mustbe efficient and result in preparations of repeatable quantityand quality (Demeke & Jenkins, 2010). Second, the initialconcentration of spoilage microorganisms is generally low,and in fermented foods target organism need to be soughtagainst a dense bacterial background (Jaykus, 2003).

Methods adapted for use with different foodstuffs mustalso be validated. In addition, validation may be requiredfor legal reasons. One of the main inconveniences thatthe food industry encounters when trying to use qPCR tech-nologies is that most of the available methods have notbeen adapted to ISO or APHA norms. It is of vital impor-tance for the expansion of the use of qPCR in the food


industry that both nucleic acid extraction methods andqPCR quantification methods be validated andstandardized.

The qPCR quantification process could serve to helpconstruct microbial growth prediction models. These couldbe very useful in the design of quantitative detection proto-cols, HACCP systems, and help in the making of accuratepredictions of shelf life (Gram & Dalgaard, 2002).

The potential of qPCR should expand as the technologycontinues to develop. For instance, the capacity to combineseveral probes labelled in such a way that they can be differ-entiated and individually quantified within the same reactionopens up the horizon for new applications. Current commer-cial technologies can discriminate up to five different fluores-cent dyes, potentially allowing for the simultaneousdetection or four different organisms plus an internal control.Automation could also maximize efficiency by reducing as-say times and the number of errors. The drawback of suchsystems is their initial price. Nevertheless, if qPCR becomesa routine technique in the food industry, the cost of automa-tion and per-sample testing should fall.

ConclusionsqPCR has proven its usefulness in basic microbiological

research. Its capacity to amplify nucleic acids from a widerange of sample types makes it an ideal system for use indifferent microbiological disciplines (Mackay, 2004). Infood microbiology and food safety, it has aroused greatinterest (Hanna et al., 2005) and several commercial kitshave been developed and validated asmethods to detect food-borne and contaminating pathogens (Makino et al., 2010).

qPCR for the quantification of food spoilage microor-ganism offers many advantages over other molecular tech-niques. Its versatility, speed, and sensitivity, together withits capacity to quantify the target organism within complexmatrices, make this technique a promising tool that couldbe used to improve the safety and quality of food products.

The identification and quantification of spoilage micro-organisms by conventional microbiological methods takesdays, but with qPCR this can be done in a matter of hours.The ability to test up to 384 samples (in some systems) ata time, each of which can be multiplexed in order to detectvarious targets simultaneously, and with no need for post-amplification processing, reduces the workload and thetime required to obtain results. The speed and efficiencyof analysis may also improve as qPCR technology evolves.For instance, FAST technology can reduce assay timesgreatly, and automation could reduce errors and the numberof personnel required to perform analyses.

An increasing number of applications are ready to betransferred from the laboratory to the food industry. How-ever, the fact that most of them are not yet validated or writ-ten into norms will probably delay their introduction.Nevertheless, their routine use for screening and quantify-ing food spoilage microorganisms would help the foodindustry improve the safety and quality of its products.

AcknowledgementsThis work was performed with financial support from

the Ministry of Science and Innovation, Spain (AGL2010-18430), and the European Community’s Seventh Frame-work Programme (KBBE-CT-2007-211441). N. Mart�ınezis the beneficiary of a JAE - CSIC contract financed bythe European Social Fund. The authors thank AdrianBurton for linguistic assistance.

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qpcr as a powerful tool for microbial food spoilage quantification: significance for food quality

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