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Relationships amongst phenyltio-carbamide sensitivity, body composition, coffee and tea consumption

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Relationships amongst phenyltio-carbamide sensitivity, body composition, coffee and tea consumption

DOI: https://doi.org/10.52091/EVIK-2022/2-1-ENG

Received: January 2022 - Accepted: March 2022


1 Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences
2 Pécsi Brewery
3 Department of Dietetics and Nutritional Sciences, Semmelweis University, Faculty of Health Sciences


taste perception, single nucleotide polymorphism, electric impedance, Body Mass Index, food preferences

1. Summary

Polymorphisms of TAS2R38 gene responsible for bitter taste perception elicit a bimodal receptor response in the population upon the detection of phenylthiocarbamide and 6-n-propylthiouracil, respectively. Genetic differences in sensitivity to phenylthiocarbamide and 6-n-propylthiouracil may affect body composition, food preferences, and frequency of consuming different food types. To date, no publication has been published in Hungary on the joint study of these factors.

The aim of the present research is to find correlations between phenylthiocarbamide taster status and body composition, and the frequency of consumption of different bitter-tasting foods.

In the study, a taster status survey of participants (n = 170), a bioimpedance-based body composition analysis (n = 96) and completed a food frequency questionnaire of bitter foods (n = 170) were conducted.

Descriptive statistical methods, cross-tabulation analysis, multiple correspondence analysis, and Mann-Whitney test were used for data analysis at 5% significance level.

The proportions of the taster and non-taster categories proved to be the same as reported by international literature (70%/30% respectively). There were no significant correlations among taster status and the other examined parameters, however, based on the multiple correspondence analysis, the observed trends are in accordance with the international literature. There were significant correlations among gender, body composition and some variables describing food preference.

Based on the literature data and our own results, there can be a relationship between genotype and body composition, and genotype and food choice. Further analyses with large-sample size and representative research are needed to substantiate these assumptions.

Abbreviations: PTC: phenylthiocarbamide; PROP: propylthiouracil; SNP: Single Nucleotid Polymorphism; GPCR: G Protein Coupled Receptor; PAV: Proline-Alanine-Valine; AVI: Alanine-Valine-Isoleucine; AAI: Alanine-Alanine-Isoleucine; PAI: Proline-Alanine- Isoleucine; PVI: Proline-Valine-Isoleucine; AAV: Alanine-Alanine-Valine; FFQ: Food Frequency Questionnaire; BIA: Bioelectrical Impedance Analysis; BMI: Body Mass Index; PBF: Percentage of Body Fat; VFA: Visceral Fat Area; MCA: Multiple Correspondence Analysis.

2. Introduction

Humans perceive their environment and its relation to them through their sense organs and senses. Five major senses are distinguished: sight, hearing, touch, olfaction, and gustation. There are further channels of sensations also known, e.g. balance, hunger, thirst, pain or discomfort [1]. Perception of taste and flavours are related to the oral and nasal area, including the sense of smell and the trigeminal sensation through the chemosensory system. It belongs to the chemical senses, and it focuses on the perception of the chemicals in our environment. Taste receptors detect the chemicals in the consumed food, which are generally called tastants. These are usually water-soluble molecules, which provide information on the quality and safety of food [2].

Taste perception is a direct contact process, which takes place in the oral cavity. The receptors can be found on the surface of the tongue, in the pharynx, on the palate and in the upper part of the oesophagus. Receptors are organized in the taste buds, which are located in the taste papillae. The sensory information is transferred through the VII; IX. and X. cranial nerves, then the brainstem’s and the thalamus’ nuclei and finally arrives to the frontal operculum and the gustatory cortex of the insula. These areas and the nuclei of tractus solitarius in the brainstem are linked with the hypothalamus and the amygdala, thus probably influencing hunger and satiety, homeostatic reactions to eating and any emotions linked to eating [2, 3].

Bitter taste often triggers a rejection, which is an innate human reaction. On one hand, this aversive reaction is due to the fact, that many bitter tasting compounds (secondary plant metabolites, e.g. alkaloids, some inorganic and synthetic compounds, and in case of food the rancid fat) are toxic, thus consuming them might be harmful, or life-threatening [4].

On the other hand, several bitter tasting compounds are known, which have beneficial effect from the pharmacological or nutritional point of view. These compounds are for example the glucosinolates and their decomposition products, the isocyanates, which are found in cabbage, broccoli or brussels sprouts (all belong to the Brassicaceae family). Coffee, tea, and cocoa contains methylated xanthine derivatives, like caffeine, theophylline, and theobromine; in beers we find the alpha-acids, which originate from the hop and are mainly responsible for the bitter taste. In case of the vegetable species, the bitter taste note might trigger rejection, in the case of the latter products; bitterness is an expected part of their sensory character [5, 6, 7].

In the field of taste perception, five basic tastes are distinguished: sweet, salty, sour, bitter and umami. This last one was accepted as a basic taste following the discovery of its specialized taste receptor in 2002 [8]. Among the five basic quality, the detection of bitter taste is the most complex; the TAS2R gene family, which consists of 25 functional genes, performs its regulation. These genes are coding the TAS2Rs receptors, which structurally bind to given bitter taste compounds (ligands), however in case of several receptors, their ligands is not identified yet [7].

Phenylthiocarbamide (PTC, also known as 1-phenylthiourea) and the 6-n-propylthiouracil (PROP) are colourless or white, crystalline, bitter tasting organic compounds: both have sulphur containing (SCN) functional group. Their use is different: phenylthiocarbamide is used as an industrial additive, colorant, while the propylthiouracil is applied as an antithyroid agent in case of hyperthyroidism [9, 10]. The structure of PTC and PROP shown in the figure 1.

Figure 1. The chemical structure of phenyl-thiocarbamide (PTC) and 6-n-propylthiouracil

Peculiarity of these two compounds, that they trigger a bimodal reaction in humans: a part of the population is able to perceive their bitter taste, while others not. Its discovery is linked to the chemist Arthur Fox. In 1931, Fox working in a laboratory of the DuPont chemical company accidentally released some fine crystalline PTC to the atmosphere of the room. A colleague working nearby complained on perceiving bitter taste. Fox did not perceive any bitter taste, despite the fact that he directly contacted the fine dust. After this occasion, he tested his family and friends, and categorized the individuals as ‘taster’ or ‘non-taster’. Laurence Hasbrouck Synder geneticist, who identified that the inheritance of the non-taster status is a recessive phenomenon according to the Mendelian genetics [11], strengthened his results.

In the 1960’s the issue of changing of PTC to PROP has risen, because of the strong, sulphuric odour of PTC. In the 1980’s toxicological information also questioned the use of PTC, so researchers started to work with PROP after the comparison of the two compounds and measuring the threshold concentration of PROP [12].

Bartoshuk and co-workers discovered in 1991, that the non-taster group gives relatively homogenous responses, while the reaction of tasters were much more different, and one of their subgroups perceived the bitter taste of PROP much more intensively. Individuals, belonging to that subgroup were called supertasters. The supertaster status is not influenced by the genotype responsible for the taster status, but this discovery resulted in a third type of classification label, medium taster [13].

Taster status is defined by some variations of the genetic domain; in this case the single nucleotid polymorphisms (SNP). SNP’s are DNA sequence variations that affect one nucleotide, which are identified between the genetic domains of two individuals belonging to the same species. Each human genome has a unique SNP pattern, but these changes might be called SNP, if they show up at least in 1% of the total population. SNP’s are usually the results of errors during the DNA replication, or caused by DNA damage. They might be located in genes (both in coding and in non-coding sections), and between genes (intergenetically), thus might cause change in structure or in functions [14].

A database (dbSNP) is collecting these SNP’s, was created in 1999 by the American National Centre for Biotechnology Information and the National Human Genome Research Institute. The number of discovered SNP’s was dramatically increased by the Human Genome Project, which mapped the whole humane genome in 2003, thus resulting a total number of more than 650 million SNP’s in the database up to date (ncbi.nlm.nih.gov/sn/) [15].

In case of PTC or PROP sensitivity the SNP’s of TAS2R28 gene (responsible for bitter taste perception) define, whether the individual perceives bitter taste or not. This gene codes a heptahelical (including seven transmembrane domain), G-protein coupled bitter taste perceiving receptor, which binds to the N-C=S group of the compounds. In this case, the gene contains 1002 nucleotides, from which 3 are functionally missense-coding SNP’s, which cause a non-synonym changes, thus modifying the structure of the coded protein.

The amino acid sequence of this protein is shown in Table 1.

Table 1. Polymorphisms of TAS2R38 gene, and the amino acids of the coded protein based on [16, 17]

The two most frequent haplotype are the PAV and AVI. Individuals having dominant PAV/PAV, or PAV/AVI diplotype are usually belong to the taster group, while the recessive AVI/AVI diplotypes are non-tasters. With a much lower occurrence (1-5%), AAI, PAI, PVI and AAV haplotypes also occur in some ethnics and populations. In case of PVI and AAV the two status is usually balanced. Based on the studies it might can be concluded that the occurrence of the taster status varies between 55% and 85%, depending on the investigated population [16, 17, 18].

In Hungary, György Forray paediatrician and György Bánkövi mathematician performed a survey on children aged 7-15, in Budapest in 1967. During their study, they applied the Harris-Kalmus method with PTC solutions in order to measure the taste threshold of the children, and thus they concluded their taster status. According to their results 67.8% of the children belonged to the taster group, but they did not find a significant correlation between gender and taster status. They have published their research in the journal Orvosi Hetilap [19].

From the anatomic point of view the polymorphysm has a relationship with the number of taste buds: tasters have more fungiform papillae and more taste pores [12].

The study of PTC and PROP sensitivity’s effect on other factors have started in the 1960’s. The psycho-pharmacologist researcher Roland Fischer (born in Hungary) was the first, who assumed that there might be a relationship between taste perception and food preference [20]. Even until now several researchers study the relationship between taster status (and its haplo- and diplotypes) and body mass index [17, 21], food preference and frequencies of different food consumption (e.g. alcoholic drinks [22, 23], vegetables, especially the Brassicales [24, 25], coffee, tea [26], sweeteners [27]), and some diseases (e.g. Parkinson- disease, gastrointestinal tumours, chronic rhinosinusitis) and their symptoms [28, 29, 30].

3. Scope

The scope of the current research is to investigate correlations between taster status, body composition and the consumption frequency of bitter tasting foods. To achieve that we have performed PTC status survey, bioimpedance-based body composition measurement and used a food frequency questionnaire focused on bitter tasting foods.

4. Methods

Data collection took place in February and March of 2019, participants were volunteers from the Food Science Faculty of Szent István University, and Faculty of Health Sciences, Semmelweis University (students and staff), altogether 170 people. In the taster status survey 170 people participated, in the body composition study we had 96 participants, the food frequency questionnaire (FFQ) was filled out by 170 individuals. All data were recorded anonymously. To link the different type of data, all participants received an individual code. Participants were informed on the data handling according to the general GDPR guidelines (Regulation (EU) 2016/679).

Taster status was defined with PTC-impregnated paper strips (Precision Europe, Northampton, United Kingdom). PTC is present at 20 micrograms per strip. Individuals were assigned to the taster or non-taster category based on their responses after tasting the paper strips.

The body composition was measured with an InBody 770 (InBody USA, Cerritos, California) device, which works based on bioelectric impedance analysis (BIA). This method relies on the different levels of conductivity of the human body’s tissues. The measurement is simple and non-invasive, which provides accurate data for several anthropometric parameters, e.g. percentage of body fat, and its distribution [31]. From the recorded data set we have used the body mass index (BMI, kg/m2), the body fat percentage (PBF, %) and the visceral fat area (VFA, cm2) for further analysis [32, 33, 34]. The FFQ questionnaire involves a list of specific foods or food types, and respondents have to indicate the consumption frequency of these items [35]. Our questionnaire was assembled including bitter tasting food types, consumption frequencies were measured with category scales. The final forms were implemented through the Google Forms platform, data recording was performed online. From the recorded data in this study we report the values concerning coffee and tea consumption, not only the frequency indices, but its type and flavorings also. In order to provide transparent data, the FFQ categories were merged into three major categories (see Table 2).

Table 2. Merging of the food frequency questionnaire categories

5. Statistical analyses

To analyse the recorded datasheet, we applied descriptive statistical methods (mean, standard deviation, percentages). Afterwards, data were transformed into category variables, thus suitable for contingency table analysis, multiple correspondence analysis (MCA) and Mann-Whitney test at 5% significance level [36]. XLStat 2020.1.3. and Microsoft® Office Excel® 2016 softwares were used for data analysis.

6. Results

6.1. Demographic parameters

55 males and 115 females participated in this study, so the ratio of genders are 32.5% male and 67.65% female. The youngest respondent was 19 years old, while the eldest was 40 years old, the average age was 23.85±3.05 years. Based on their residence 44.70% lived in the capital of Hungary (Budapest), 55.30% lived in other locations. In the latter group 24.46% lived in Pest County (relating it to the total data that was 13.53%). There were only two Hungarian counties (Zala and Csongrád-Csanád) which were not indicated in any of the respondents.

6.1.1. Taster status

The distribution of taster status data (Table 3.) showed that 72.94% of the respondents were tasters, while 27.06% were non-tasters. The ratio of non-tasters among males was 23.63%, while in case of females it was 28.69%. Based on the results of the contingency table analysis there is no significant relationship between the gender and the taster status (χ2(1, n=170)=0.483, p=0.48).

Table 3. Results of the taster status survey according to genders and in total (number of individuals, n=170) Results of investigation of body composition analysis and its relation to the taster status

Body composition analysis was performed in case of 23 males and 73 females, altogether on 96 individuals. The averaged data of these values are listed in Table 4.

Table 4. Averaged values of the body composition data (average ± standard deviation, n=96)

BMI data showed that among the males 11 individuals were obese (BMI from 25.0 to 29.9) and three individuals were overweight (BMI > 30.0). The percentage of body fat values showed obesity in case of 6 people (PBF > 27%), while the visceral fat are was higher than the upper limit of 100 cm2 value in the case of 5 people.

Among the females the BMI showed undernourishment for 5 individuals (BMI < 18.5), 7 were obese, and 3 were overweight. The percentage of body fat data showed that 18 people was obese, and the visceral fat area was higher than 100 cm2 for 15 participants.

Based on the statistical evaluations we did not find significant relationships in case of any of the obesity-indicating parameters and the taster status (BMI: χ2(3, n=96)=0.42, p=0.93; PBF: χ2(1, n=96)=0.45, p=0.50; VFA: χ2(1, n=96)=0.01, p=0.90). The multiple correspondence analysis results on Figure 2 shows that the obesity indicating parameters have relationships with each other. The patterns show that non-tasters are positioned closer to the categories of normal body composition and body weight. Outcomes of the contingency table analysis showed that on the basis of BMI values the ratio of overweight individuals (compared to the normal weighted ones) were significantly higher among males, than among females (χ2(3, n=96)=21.52, p<0.0001).

Figure 2. Results of multiple correspondence analysis for taster status, gender, and body composition parameters (n = 96, p=0,05). Abbreviations: BMI = Body Mass Index; PBF = Percent Body Fat; VFA = Visceral Fat Area Relationship of coffee consumption and taster status

Among the FFQ respondents, 27 individuals do not consume coffee, so their data was removed from the analysis. Flavouring categories were the following: ‘with milk’ (referring to the use of milk, dairy products, or milk substitutes) and ‘with sweetener’ (referring to the use of any sweeteners (sugar, natural or artificial sweeteners). The ‘mixed’ coffee variety indicated the consumption of both Arabica and Robusta (individually or as a blend). From the 143 consumers 24 individuals drink their coffee black (without sweetener, milk, or milk substitute).

Based on the contingency table analysis there is no significant relationship among taster status and coffee consumption (χ2(1, n=170)=0.02, p=0.88), consumption frequency (χ2(1, n=143)=2,57, p=0,10) and the consumed type of coffee (χ2(3, n=143)=4.21, p=0.24). Similarly there was no significant relationship between the type of consumption, like black (χ2(1, n=143)=0.60, p=0.43), with milk (χ2(1, n=143)=0.28, p=0.59) or sweetened (χ2(1, n=143)=0.17, p=0.67) and the taster status.

The patterns of multiple correspondence analysis (Figure 3) shows that non-tasters consume coffee less frequently than the tasters, and they are unable to specify the type of coffee they consume. When the non-tasters consume coffee, they prefer the sweetened way. Tasters use Arabica type, and they usually do not add sweetener to it. Even if they add milk, it is not necessarily means the addition of sweetener. There is a clear distinction among genders: there are significantly more coffee consumers among women (χ2(1, n=143)=3.65, p=0.05), furthermore females have their coffee with milk and sweetener, while males prefer to drink it without milk (black). This is supported with the outcomes of contingency analysis (drinking coffee black: χ2(1, n=143)=3.46, p=0.05; with milk: χ2(1, n=143)=6.51, p=0.01).

Figure 3. Relationships between coffee consumption and taster status and gender (n = 143, p = 0.05) Abbreviations: ‘Milk ‘= flavored with milk, milk replacer, dairy product, ‘Sweetened’ = flavored with any sweetener (sugar, artificial and natural sweeteners), ‘Type of coffee’ - Assorted: consumed alternately or as a blend (Arabica) Relationship among taster status and tea consumption

Fourteen respondents reported that they do not consume tea, so their results were not analysed. The major categories were ‘Several types including black tea’ (consuming several tea types, including black tea); ‘Several types, but no black tea’ (consuming regularly other type of tea than black). The ‘Sweetened’ label refers to the use of any sweeteners (sugar, artificial and natural sweeteners) for tea consumption.

The ‘Flavouring – Variegated’ category means the use of several ways of flavouring (sometimes with sugar, with lemon and sometimes without sugar), while the ‘Flavouring – More items’ refers to the use of sweetener and lemon. Among the 156 tea consumers 57 individuals drink their tea without flavouring (no sweetener, no lemon added).

During our analysis we did not find significant relationship among taster status and tea consumption (χ2(1, n=170)=1.26, p=0.26), its frequency (χ2(1, n=156)=0.95, p=0.32), the consumed tea types (χ2(5, n=156)=2.57, p=0.76) and the flavouring types of the tea (χ2(4, n=156)=5.13, p=0.27). There were also no significant differences among genders.

Pattern of the multiple correspondence analysis (Figure 4) shows that females and tasters consume tea more frequently, especially black teas and herbal infusions, both flavoured, or non-flavoured. Males and non-tasters consume tea less frequently, they prefer green tea, flavoured with lemon and sweetener, or only with lemon. It was not typical among the respondents that they might consume only fruit infusions.

Figure 4. Correlations of tea consumption with taster status and gender (n = 156, p=0,05) Abbreviations: ’Tea type’ – Several types including black tea: consumption of several tea types, including black tea; ’Tea type – Several types, but no black tea’: consumption of several tea types, except black tea; ’Sweetened: with any sweeteners’ (sugar, artificial and natural sweeteners); ’Flavouring – Variegated’: occasionally different flavouring (sometimes sweetened and / or lemon, sometimes unflavoured); ’Flavouring - More items’: flavouring with both sweetener and lemon.

7. Discussion

The ratio of tasters and non-tasters in our study is in accordance with those reported in the literature, namely 70% vs. 30% in the American and Caucasian population [6, 37]. We did not find relationship between taster status and BMI value, similarly to previous studies [17, 38]. Contrary to these results, some researchers were able to find significant correlations among these parameters [39]. Generally, the results on this field are controversial; there is no consensus among the researchers. Our new outcomes did not show relationships between taster status, body fat percentage and visceral fat area. However, our results showed significant differences between the genders in the overweight BMI category. The reason behind this is the muscle weight of the two genders: the BMI does not differentiate between fat tissue and non-fat tissue and does not take into consideration the distribution of body fat. Therefore, the BMI value’s specificity is high, but its sensitivity is low [40]. In case of the male participants the skeletal muscle mass was significantly higher (Mann-Whitney U=1664, n1 =23, n2 = 73, p<0.0001, two-sided), so more of these individuals were put into the overweight category.

Although we did not find significant relationships in case of coffee consumption, we have observed trends, patterns according to the multiple correspondence analysis. Non-tasters consume coffee less frequently, and they are unable to specify its exact type. These two factors are probably related to each other, since those people who are less interested in coffee consumption, are also less interested in the exact type of coffee. When these individuals consume coffee, they usually add sweeteners, this is less typical in case of tasters, which is supported with literature data [41]. The difference among genders in flavouring or not flavouring the coffee might be related to a social expectation, that the espresso shot is more masculine, while the latte type drinks (e.g. milk espresso) is more feminine [42].

In case of tea consumption, we did not find significant relationships, but several trends were recognized, which are in accordance with the international literature, stating that tasters prefer green tea in a smaller extent [43, 44].

The limitation of our study, that it was not representative from the demographic point of view. During the tests, we have worked with commercially available paper strips, while using PTC or PROP solutions might lead to results that are more precise.

8. Conclusions

Both literature data and our own results show that there might be some level of relationships among genotype, body composition and food choice. It is very likely, that not the genotype, but the phenotype (taster - non-taster) will be the factor which indirectly, through the food choice and food preferences might contribute to obesity, and its related diseases. Since eating habits and food preferences are influenced by other factors (like sociodemographic or psychological ones), these effects might overwrite the expected consequences of the phenotype (preference or aversion toward bitter taste). Furthermore, representative studies with larger sample size are necessary to confirm these hypotheses.

9. Statements

Financial support: The project was supported by the grant EFOP-3.6.3-VEKOP-16-2017-00005. It was also supported by the Ministry of Innovation and Technology grant number ÚNKP-19-3-I-SZIE-65 New National Excellence Program. The authors thank the support of the National Research, Development, and Innovation Office of Hungary (OTKA, contracts No FK 137577).

Contribution of authors: Experimental design: BB, AL, MVB, AG; Data acquisition: BB, DK, AL, MVB, ZK; Data analysis: BB, AG; Preparation of manuscript: BB, AG, ZK; Supervision and approval of manuscript: BB, AG, DK, AL, MVB, ZK.

Conflicts of interest: The authors have no conflicts of interest.

Acknowledgements: Barbara Biró thanks the support of the Hungarian University of Agriculture and Life Sciences, Doctoral School of Food Science. Attila Gere thanks the support of the Premium Postdoctoral Program and the National Research, Development and Innovation Office (project number K134260). The authors thank the cooperation of the test participants.

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Characterization of Serratia species and qualitative detection of Serratia marcescens in raw and pasteurized milk by an analytical method based on polymerase chain reaction

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Characterization of Serratia species and qualitative detection of Serratia marcescens in raw and pasteurized milk by an analytical method based on polymerase chain reaction

DOI: https://doi.org/10.52091/EVIK-2021/2-4-ENG

Submitted: July 2020 – Accepted: December 2020


1 Hungarian Dairy Research Institute Ltd, Mosonmagyaróvár
2 Széchenyi István University, Wittmann Antal Multidisciplinary Doctoral School in Plant, Animal, and Food Sciences, Mosonmagyaróvár
3 Széchenyi István University, Faculty of Agricultural and Food Sciences, Department of Food Science, Mosonmagyaróvár


nosocomial infection, Serratia species, Serratia marcescens, pathogen, prodigiosin, pigment, polymerase chain reaction (PCR), food diagnostics

1. Summary

Serratia species are opportunistic pathogenic microorganisms primarily known as nosocomial infectious agents, which can also cause food quality problems. The appearance of the extracellular pigment-producing Serratia marcescens in cow’s milk causes its red discoloration, posing a challenge to the dairy industry and food certification laboratories. The detection of the bacterium by conventional procedures based on microbiological methods is time-consuming and labor-intensive, and in many cases does not lead to satisfactory results due to the competitive inhibitory effect of the accompanying microflora. Following the analysis of the relevant literature, the published endpoint PCR methods and the primers used for the detection of S. marcescens were evaluated in in silico and in vitro assays, and then the procedure was tested on farm milk samples. Using the method, a total of 60 raw and pasteurized milk samples were analyzed, more than half of which (i.e., 32) were identified as S. marcescens positive. The significance of our work is mainly represented by the application of the published test methods in food industry practice. Our results highlight to the importance of detecting this bacterial species.

2. Introduction and literature review

Nowadays, the impeccable quality and long shelf life of foods is a basic requirement of consumers. Accordingly, there is a growing demand for ever faster, more accurate and more reliable food diagnostic procedures. In this context, molecular diagnostic methods are gaining ground, for example in the rapid detection of pathogenic microorganisms. Polymerase chain reaction (PCR)-based diagnostic kits suitable for the identification of pathogenic microbes are produced by many manufacturers, and these are also used successfully in Hungarian food testing laboratories. These molecular biological tests are mainly suitable for the detection of microbes hose presence poses a high risk to public health (e.g., Escherichia coli, Salmonella Typhimurium, Listeria spp.). Less attention is paid to pathogens that are not required to be tested by law, such as Serratia species present in raw and pasteurized milk.

Serratia species are found in many places in our environment [1]. They are saprophytes or opportunistic pathogens [2], facultative anaerobic, biofilm-forming organisms [1, 3]. S. marcescens grows particularly well in phosphorus-containing environments (e.g., soaps, shampoos) and is also resistant to certain disinfectants [4, 5], so it can cause various nosocomial diseases [6, 7, 8]. Increasing antibiotic resistance of S. marcescens has also been reported in the literature [8, 9, 10]. The bacterium therefore survives and grows easily, so it may find its way into foods under inadequate hygienic conditions. Presumably, it can enter drinking milk as a result of violating hygiene rules, it can grow there and degrade the quality of food [1, 11, 12]. For some species, spoilage is indicated by a characteristic red hue.

In the case of the Hungarian dairy sector, accurate data are not available on the extent of the prevalence of Serratia species and S. marcescens, and on which species cause the infections and degrade milk quality. Nor is there a Hungarian survey on the extent of Serratia contamination of dairy farms. With the exception of a few publications, the available information on the exposure of the dairy industry to Serratia is also lacking at the international level. Such exceptions are a scientific article on the epidemic of mastitis caused by S. marcescens at Finnish diary farms [1], and an older report discussing the role played by pigment-forming Serratia species in mastitis [13].

The following Serratia species may be responsible for the red discoloration of milk: S. marcescens, S. rubidaea, S. plymuthica and S. nematodiphila (Table 1). According to their incidence, S. marcescens is of greater importance. Their characteristic pigment is the red prodigiosin, a water-insoluble secondary metabolite that is produced under specific environmental conditions [14, 15, 16, 17] (Figure 1). The typical red colonies appearing on the culture medium alone do not provide sufficient information to identify Serratia, as certain species of many other genera, not belonging to Enterobacteria, may also produce prodigiosin [14, 18].

Table 1. Characterization of Serratia species and their pigment production [19–22]
Figure 1. Pure culture of Serratia marcescens on tryptone-soy agar (TSA) (30 °C, 48 h)

There is currently no ISO standard for the detection of Serratia species in foods. In their 2006 book chapter [9], Grimont and Grimont discuss the characteristics of the genus Serratia, as well as aspects of their isolation and identification. However, identification by classical microbiological methods is rather cumbersome and often ineffective due to the inhibitory effect of the accompanying flora, despite the fact that the pink discoloration of the milk sample is clearly visible to the naked eye. Although culture media are available for the selective growth of the bacterium [47], in practice their use does not provide a satisfactory solution. In addition, conventional methods are time and labor intensive.

There are commercially available rapid methods for the determination of S. marcescens, for example the miniaturized test kit from bioMérieux called Rapid ID 32 E, which satisfies the requirements of standard ISO 7218 [48]. However, a colony growing on a culture medium is required to perform the test. Diagnostic tests based on the PCR method, as mentioned before, could provide a solution to overcome the difficulties of detection. At present, however, only the Genesig product of Primerdesign can be mentioned as a molecular diagnostic kit for the detection of S. marcescens [49].

The literature relevant for the food industry and, in particular, the dairy industry, is rather poor on the detection of Serratia species, including S. marcescens, by either endpoint PCR or real-time PCR methods. Hejazi et al. [50] carried out the serotyping of S. marcescens by the RAPD-PCR technique. Serological samples from patients in need of hospital care were used in their study. Iwaya et al. [6] also tested blood samples for S. marcescens strains using a real-time PCR method. Zhu et al. [51] performed molecular characterization of S. marcescens strains by RFLP and PCR methods, while Joyner et al. [2] detected S. marcescens strains in marine and other aquatic environmental samples (e.g., coral mucus, sponge pore water, sediment, sewage, wastewater and diluted wastewater) by real-time PCR. A study of Bussalleu and Althouse, published in 2018, reports a conventional endpoint PCR technique suitable for the identification of S. marcescens that effectively detects the presence of the microorganism in wild boar semen [52].

Our goal was the set up a classical PCR method suitable for the detection of S. marcescens in milk. The significance of our work lies in the fact that PCR-based methods described in the literature and the primers used were analyzed, then the procedure deemed appropriate was adopted to food hygiene analytical practice. In our experiments, qualitative determination of the possible S. marcescens contamination underlying the discoloration of factory, raw and pasteurized milk samples was performed.

3. Materials and methods

3.1. In silico studies

Based on the literature, three primer pairs (Table 2) were selected, which were evaluated by computer modeling, by so-called in silico analysis, as well as in vitro experiments in order to find the most suitable one for subsequent PCR assays.

Table 2. Serratia marcescens-specific primer pairs used in this study

In our in silico studies, the specificity of the a primer sequences was verified by comparison with a DNA database (NCBI BLAST) [54]. Comparison with the database allows for homology search (“blasting”). Following this, the suitability of the primers, i.e., whether a possible PCR reaction takes place with the selected genomes, was tested with a molecular biology software (SnapGene 5.1.5.) [55]. In the latter case, positive and negative control genomes were downloaded from the NCBI database, and then the SnapGene software was used, in an in silico way, to investigate whether the PCR reaction would take place with the primer pairs. The positive and negative controls used for reference purposes were whole chromosome genomes (Table 3).

Table 3. Genomes of bacterial strains used as positive and negative controls in in silico analyses and their reactions to primer pairs

* Primerek: A. Fpfs1 és Rpfs2; B. FluxS1 és RluxS2; C. Serratia2-for és Serratia2-rev.


3.2. In vitro experimental studies

To confirm the results of the in silico studies, in vitro were performed in which the selected primer pairs were tested in laboratory PCR analyses on genomic DNA samples of selected strains of bacteria (several S. marcescens strains were used as positive control and Lactobacillus delbrueckii subsp. delbrueckii, Streptococcus thermophilus, Enterococcus faecalis and Micrococcus luteus were used as negative controls). The microorganisms were bacterial strains belonging to the collection of MTKI Kft. and coming from factory environment, determined by genetic identification.

When putting together the components required for the PCR reaction, 5.2 µL of PCR grade sterile water, 10 µL of DreamTaq Green 2× PCR Master Mix (Thermo Fisher Scientific, Waltham, Massachusetts, USA), 0.4 µL (10 pmol/µl) primer and 4 µL of isolated bacterial genomic DNA were used for each reaction. The negative control of the reactions was PCR grade sterile water. The program parameters of the PCR instrument (Mastercycler Nexus Gradient; Eppendorf International, Hamburg, Germany) were as follows: 95 °C for 1 minute, then for 40 cycles 95 °C for 15 seconds, 59.5 °C for 15 seconds, 72 °C for 10 seconds and, finally, 72 °C for 7 minutes [52].

For size separation of the DNA segments formed during the PCR reaction, a 10 µL sample was analyzed on a 2% agarose gel [TBE buffer (Tris-borate-EDTA) (10×), Thermo Fisher Scientific; Agarose DNA Pure Grade, VWR International, Debrecen, Hungary; ECO Safe Nucleic Acid Staining Solution 20.000×, Pacific Image Electronics, Torrance, California, USA]. The DNA size marker was the GeneRuler Low Range DNA Ladder (Thermo Fisher Scientific). Gel documentation was performed using the Gel Doc Universal Hood II gel documentation equipment and software (Bio-Rad, Hercules, California, USA).

3.3. analysis of raw and pasteurized milk samples

On the one hand, we used in our study factory raw and pasteurized milk samples in the case of which S. marcescens contamination was suspected due to their pink discoloration. On the other hand, factory raw and pasteurized milk samples that arrived at the laboratory together with the above samples but not exhibiting discoloration were also tested.

For the DNA digestion and purification process, the NucleoSpin Microbial DNA kit (Macherey-Nagel, Düren, Germany) was used according to the manufacturer’s instructions. The reaction tubes containing the eluted DNA were stored in a freezer at -20 °C.

Next, the suitability of DNA isolation and the amplifiability of the samples were checked by 16S rDNS polymerase chain reaction, using primers 27f (5’-AGAGTTGATCMTGGCTCAG-3’) and 1492r (5’-TACGGYTACCTTGTTACGACTT-3’). The total volume of the PCR reaction for 1 sample was 5.6 µL of PCR grade sterile water, 10 µL DreamTaq Green 2× PCR Master Mix, 0.2 µL (10 pmol/µl) of the primers and 4 µL of isolated bacterial genomic DNA. The negative control of the reactions was PCR grade sterile water. The program parameters of the PCR instrument were as follows: 95 °C for 4 minutes, then for 40 cycles 95 °C for 20 seconds, 54 °C for 30 seconds, 72 °C for 1 minute and, finally, 72 °C for 5 minutes.

For the separation of the DNA segments formed during the PCR reaction, a 5 µL sample was analyzed on a 1% agarose gel. The DNA size marker was the GeneRuler 1 kb Plus DNA Ladder (Thermo Fisher Scientific). The DNA sample tested was judged to be suitable for further PCR analysis if the length of the copies of the amplified DNA fragment was as expected (~1500 bp).

In the next step, samples were subjected to S. marcescens-specific PCR analysis and gel electrophoresis as described in subsection IN VITRO EXPERIMENTAL STUDIES. The results were evaluated on the basis of the presence/absence principle.

In order to check the suitability of the method, PCR results of the milk samples were compared with the few available API (bioMérieux, Budapest, Hungary) test results in a control test. The method was then used to detect the presence of S. marcescens in raw and pasteurized milks.

4. Results

In our in silico studies, when examining the homology of the primers, they showed similarity primarily to S. marcescens chromosome genomes. However, matches were also found in the case of S. rubidaea and S. nematodiphila strains and some non-Serratia species. These results were taken into account during the selection of reference genomes designed for our SnapGene software studies. The need for further investigation was justified by the fact that appropriate homology or the matching of the basis do not automatically mean that the PCR reaction will take place, because the direction of the primers, their melting temperature and the size of the PCR product formed are also critical, among other things.

In the SnapGene test, PCR reactions were predicted with the following parameters: our analyses were performed with at least 15 bases matching and the exclusion of single isolated mismatches. The minimum melting temperature was 50 °C and the maximum length of the fragment obtained as the result of the amplification was 3 kbp.

As shown in Table 3, when matched with the S. marcescens genomes, the primer pair Serratia2-for and Serratia2-rev showed amplification in all cases. The PCR reaction generally resulted in six or seven amplicons on the 16S rDNA sections. The adhesion site of the Fpfs1–Rpfs2 and FluxS1–RluxS2 primer pairs is located outside the 16S rDNA in most S. marcescens strains, but in some cases they did not show in silico amplification, so their sensitivity did not prove to be adequate. In the negative control genomes, the completion of a PCR reaction was predicted by the primer pair Serratia2-for and Serratia2-rev in some cases for certain S. rubidaea and S. nematodiphila strains. Using primers Fpfs1–Rpfs2, the PCR reaction would take place in the case of a S. nematodiphila strain. Primers FluxS1–RluxS2 did not predict the occurrence of a reaction on any of the selected negative control genomes (Table 3).

In S. marcescens genomes selected as positive controls in in vitro experiments, all three primer pairs gave signals according to the expected fragment size, and none gave a signal on the negative controls. The analysis carried out with the primer pair Serratia2-for and Serratia2-rev is shown in Figure 2. In the case of negative samples, the weak signals at around 50 bp are caused by the accumulation of the byproduct aspecific DNA fragments, primer dimers.

Based on the results of in silico analyses and in vitro studies, primers Serratia2-for and Serratia2-rev were considered to be suitable for further work, despite the fact that their specificity was not perfect. The decision was based on the probable frequency of occurrence of S. marcescens on the one hand and the importance of avoiding samples with false negative results on the other.

In order to check the suitability of the method that had been set up, factory milk samples were tested in a control study. Some of the milk samples (n=10) exhibited pink discoloration. Using our test method, nine samples were found to be positive for the microbe sought. We also had API test results for four of the samples. The four API-positive samples were also found to be positive in the PCR assay. The method was then used to detect S. marcescens in raw and pasteurized milks.

Some of the milk samples showed peach-pink discoloration (Figure 3), but it was not clear in many cases due to the pale or yellowish tint. A total of 60 samples were analyzed. Of these, 32 (53.3%) gave positive results and 28 (46.7%) gave negative results for the presence of S. marcescens.

Figure 4 shows the result of one of our assays, the separation by gel electrophoresis. It can be clearly seen that the positive control strain gave a positive signal, while the negative control sample gave a negative signal, and positive signals were obtained for three test samples. The weak signals appearing in the case of negative samples are again caused by the accumulation of primer dimers.

Figure 2. Results of PCR analysis with Serratia2-for and Serratia2-rev primers on the genome of selected bacterial strains. Lanes: 1. Serratia marcescens 551R; 2. Serratia marcescens 1911; 3. Lactobacillus delbrueckii subsp. delbrueckii 0801; 4. Streptococcus thermophilus 1102; 5. Enterococcus faecalis 1101; 6. Micrococcus luteus CLTB1; 7. Negative control (sterile water); M: Molecular weight marker
Figure 3. Milk samples. Left sample is netive and right sample is positive for Serratia marcescens, based on the result of PCR test
Figure 4. Gel electrophoresis image of Serratia marcescens-specific PCR assay. Lanes 1 to 7: Milk samples; K+: Positive control (genomic DNA from Serratia marcescens); K-: Negative control (sterile water); M: Molecular weight marker

5. Discussion

When evaluating our results, it is important to take into account that the PCR analysis is a method suitable for the amplification and detection of the target DNA in the sample, based on which it is not possible to determine whether the amplified S. marcescens-specific DNA comes from viable, dead or so-called VBNC cells. In the VBNC (“viable but not culturable”) state, the cells are viable, metabolically active, but cannot be propagated by classical culture methods. This condition is reversible.

The objective of our work was to establish a classical PCR method for the detection of S. marcescens. Using the test procedure applied, qualitative determination of the S. marcescens contamination responsible for the discoloration of milk samples can be carried out.

Although the experiments presented here focused on the detection of pigment-producing S. marcescens, a future genus-level study could identify all 20 Serratia species (Table 1). The significance of the detection of other Serratia species is evidenced by the fact that, although the genus Pseudomonas is the main cause of the spoilage of chilled raw milk, the dangers of Serratia species in this respect are also known [56]. In addition to Pseudomonas strains, Serratia strains have also been identified in many cases as causes of milk spoilage. Members of the genus Serratia have been detected in dairy plants [3, 12], in raw milk samples stored at 4° C [56, 57, 58] and in milk containers [59]. It was noted by Grimont and Grimont [9] already a decade and a half ago that raw milk lots can occasionally be contaminated with Serratia species, and the species most often occurring in diary products are S. liquefaciens and S. grimesii.

The presence of psychotrophic Serratia species (e.g., S. liquefaciens) in raw milk can cause spoilage even after heat treatment. Baglinière et al. found that the thermally stable Ser2 protease produced by S. liquefaciens may be a significant factor in the destabilization of UHT milk [11, 60].

In conclusion, it can be stated that a genus-level study would be an interesting research project that would fill a gap, and which would allow the monitoring of raw milk in this respect, the wide detection of Serratia species. Presumably, the results would provide useful information not only to the stakeholders of the dairy economy and the dairy industry, but could also have an impact on Hungarian regulatory and monitoring practice.

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