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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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Initial microbiological experience in small-scale fruit beer product development

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Initial microbiological experience in small-scale fruit beer product development

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

Received: December 2021 – Accepted: March 2022


1 Novel Food Kft.
2 Eurofins Food Analytica Kft.


Beer, bottling machine hygiene, small-scale brewing, lactic acid bacteria, Enterobacteriaceae, Bacillus, Pectinatus, Megasphera, wild yeast, fungi, CIP cleaning system, alpha acids

1. Summary

The market share of small-scale breweries in the total Hungarian beer market was 3 percent in 2020 [1]. The goal of the law affecting the sale of small-scale beers (the so-called “Beer Act”, published in Issue 275 of 2020 of the Hungarian Gazette on December 11, 2020) is to create an opportunity for small-scale breweries to gain a better market position [2]. The measure is expected to have a positive effect on the trends that have been going on in Hungary for years, such as the increase in the number of market participants, the expansion of the product range and the increase in consumer interest.

In addition to the above encouraging trends, as consumers, we find that, on average, small-scale breweries lag behind large-scale producers in terms of producing a constant high quality and in ensuring the stability and shelf life of the bottles of beers. The quality deficit mentioned is mainly due to the deficiencies in the quality management systems of small breweries, the inadequate level of expertise available and the specific sales conditions.

In this article, small-scale product development of a fruit beer representing one of the most sensitive product categories in terms of packaged product stability because of its low alcohol content and, at the same time, high sugar content is presented. Mainly the experience related to the achievement of microbiological stability is summarized in the paper, while also dealing with the development of the manufacturing environment, summarizing the most important sources of danger and possibilities for failure, and drawing the attention of existing and future manufacturers to the possibility that the certificates of conformity of manufacturers of brewing equipment do not always guarantee their proper functioning, and in many cases they may have to be reviewed and modified. The microbiological relationships mentioned in our manuscript are based on our own observations. The product-specific test methods used in the course of the project are also presented in detail.

2. Introduction

2.1. Small-scale brewing

In legal terms, breweries that produce less than 200,000 hectoliters of beer per year has been called small-scale breweries in Hungary since 2017. Regulation before 2017 drew the line at 8,000 hectoliters, under which breweries benefited from a 50% excise tax rebate [3].

2.2. Fruit beers

The category fruit beer includes beers that are made with some kind of fruit or a combination of several fruits. Here the word fruit is used in a culinary rather than a botanical sense: fleshy, seed-associated plant structures that are sweet or sour and can be eaten raw. These include, for example, pome fruits (apples, pears, quinces), stone fruits (cherries, plums, peaches, apricots, mangoes, etc.), as well as fruits that have “berry” in their English names (strawberries, raspberries, blueberries), currants, citrus fruits, dried fruits (dates, prunes, raisins, etc.), tropical fruits (banana, pineapple, guava, papaya, fig, pomegranate, cactus figs, etc.) [7].

Flavored beer: Beer for which other flavoring substances may be used instead of or in addition to hops to create a flavor effect. The detailed characteristics of these products are recorded in the product data sheet.

In the case of flavored beers, the flavoring substances are added to the wort or the beer during the brewing operations, at the latest during maturation or filtration. As a result of the flavoring substance added during maturation or filtration, the original gravity of the finished beer may not increase by more than 1/3 [8].

2.3. Launching production in a small-scale brewery

Ideally, the main sub-processes of launching production in a small-scale brewery are as follows:

  1. Conducting official licensing procedures
  2. Construction of the production plant and auxiliary facilities
  3. Product development
  4. Installation of brewing technology
  5. Product manufacturing
  6. Product sales

It is important to emphasize that during an efficient and cost-optimized production launch, product development precedes the acquisition of brewing technology, a sub-process specifically based on the experience of the former. This sequence can be achieved with the involvement of a service organization specializing in product development, which has the professional and technological background required for the process.

2.4. Technological equipment involved in our project

For the small-scale production of fruit beer, the following main technological equipment were installed:

  • Malt mill
  • Mash house equipment
  • Combined mashing/filtering tub
  • Universal hop kettle - Whirlpool tub
  • Electric control panel for the brewing process
  • Wort cooling and recuperation equipment
  • Heat supply equipment
  • Mash house auxiliary equipment
  • Fermentation area equipment
  • Barrel washing and filling equipment
  • Diatomaceous earth filter
  • Beer pasteurization equipment
  • Bottling machine
  • Compressed air supply equipment
  • Refrigeration technology equipment
  • Brewery ancillary equipment

In the above list, equipment which is specifically used to ensure or improve the microbiological stability of beer or have an above-average effect on it are highlighted.

3. Microbiological production control

3.1. Microbiological stability of beer

The biological stability of beer is compromised by any microorganism that is able to multiply in beer, cause turbidity or form bottom sediments, and damage the beer through its metabolites. The number of these microorganisms is small, as only lactic acid bacteria and yeasts are able to grow under the given anaerobic conditions due to the alcohol content, carbon dioxide content, bitterness and low pH of beer. There is a certain period of time between the infection and turbidity caused by these microorganisms and the appearance of the bottom sediment, the length of which depends on the degree of infection, the virulence of the organisms, the quality of the beer, the access of oxygen and the storage temperature.

Microbiological stability can be ensured by the use of biologically sound adjusting yeasts with high fermentation potential, the concentrated culture of which and the thorough washing, cleaning and disinfection of the tanks, lines and equipment have been checked.

Automatic cleaning equipment deserves special attention. Sharp filtration, together with pumping with the exclusion of ambient air and the use of containers cleaned with sufficient thoroughness, allows the beer to be dispensed without pasteurization. Close microbiological control is required at each stage, such as fermentation, maturation, filtration and pumping. [4]

3.2. Factors influencing the microbiological stability of beer

From a microbiological point of view, beer is a relatively stable beverage. The beer parameters that contribute to this stability are as follows:

  • Ethanol content (up to 10%, sometimes even higher): exposure to 5% ethanol has been shown to increase the permeability of the cell membrane and thus to interfere with the proton-driving force across the membrane (which is important for energy production). This means that most microbes do not survive or multiply in beer at this alcohol level.
  • Carbon dioxide content (~0.5% v/v): dissolved CO2 creates an anaerobic environment, preventing the growth of microorganisms that cause aerobic deterioration.
  • Low pH (pH 3.8-4.7): many microorganisms are unable to grow at low pH (pH<5) because they cannot maintain intracellular pH homeostasis at these low pH values.
  • Iso-alpha acids (15-100 µg/L, the concentration may be different from this): iso-alpha acids exert an antimicrobial effect by increasing the permeability of bacterial cell membranes.
  • Decreased nutrient availability (most fermentable sugars are metabolized by yeast): many important nutrients, such as carbohydrates, amino acids and some vitamins B are present in very low concentrations in beer as they are consumed by the yeast during fermentation. Any increased nutrient levels (e.g., carbohydrates in low-alcohol beers) pose a risk of proliferation of microorganisms that cause spoilage.
  • Low oxygen content (preferably below 0.1 µg/L): anaerobic conditions reduce the risk of potential growth of microorganisms that cause aerobic spoilage.

In modern brewing, a number of techniques are used to prevent the entry of microbiological contaminants or their survival during the brewing process, as well as during filling/packaging, in order to increase microbiological stability. Some examples:

  • Boiling the mash, pasteurization, or sterile filtration before packaging.
  • Well-designed brewing equipment that resists aggressive hygiene practices, such as CIP (Clean-In-Place) cleaning.
  • Elimination of many traditional (and microbiologically risky) production processes (e.g., spontaneous fermentation or open fermentation vessels).

3.3. Causes of infection

Pediococcus cerevisiae in the form of mono- and diplococci, or tetracocci, clouds the beer and gives it an acidic, diacetyl taste reminiscent of butter.

Lactic acid bacteria produce lactic acid, formic acid and acetic acid. They also cause turbidity and, in part, form bottom sediment.

Wild yeasts are rare. They make the beer cloudy, form a juicy bottom sediment and also impart a mostly aromatic, distinct, partly coarsely bitter taste.

Cultured yeasts cause turbidity, bottom sediment, or only separate yeast colonies in the pumped off beer. Even if they remain only imperfectly in the beer after filtration, they can multiply after the rich oxygen uptake during pumping, especially if there is a large difference between the final degree of fermentation of the beer and the dispensed degree of fermentation [4].

3.4. Spoilage microorganisms

3.4.1. Microorganisms most often associated with brewing and beer

Each raw material (e.g., malt, hops, water or additives) carries its own specific microorganisms. The proliferation of these microorganisms during one of the brewing steps results in the formation of metabolites that cause aftertastes. In the event that these microorganisms survive all steps of the brewing process, including pasteurization, if used, they may be present in the bottled beer as potential spoilage agents. Yeast used for the fermentation can also be a source of contamination.

It has been observed that during yeasting, the yeast can be contaminated with small amounts of bacteria and wild yeast. To avoid this, proper treatment of brewer’s yeast is required.

Additional sources of contamination can be the brewing equipment (vessels, lines) if they are not properly cleaned and maintained. Until packaging is completed, the final steps in the manufacturing process (after fermentation) may also be prone to contamination by microorganisms that are airborne or present in the filling apparatus (e.g., due to high humidity).

Spoilage microorganisms most often found in breweries and in beer are listed in Figure 1.

Figure 1. Most common beer spoilage microorganisms during the various steps of the brewing process and in the finished product. Orange arrows indicate the steps of the manufacturing process where the microbial load is reduced by heat treatment (wort boiling and pasteurization). [2]

Contaminating bacteria in beer are mostly lactic acid bacteria belonging to the genera Lactobacillus and Pediococcus (accounting for more than 80% of the bacterial infections in beer), but other anaerobic bacteria such as Pectinatus and Megasphaera are sometimes also found in spoiled beer. [2] Lactic acid bacteria [6]

Lactic acid bacteria are strictly fermentative, facultative anaerobic Gram-positive, non-spore-forming rods or cocci that belong to the order Lactobacillales. Most Gram-positive bacteria are inhibited by iso-alpha acids however some are resistant to these antibacterial compounds. The two most common lactic acid bacteria in beer are Lactobacillus brevis and Pediococcus damnosus. These bacteria produce acetic acid and lactic acid, and also compounds responsible for various aftertastes, such as diacetyl (“buttery” flavor). Pediococcus in particular is known to produce large amounts of vicinal diketones. Pediococcus also has a relatively high alcohol tolerance: it can proliferate even at ethanol concentrations above 10%. In addition, lactic acid bacteria also produce exopolysaccharides (EPS), which cause so-called silky turbidity in beer due to the increased viscosity and mucous appearance.

The most important Lactobacillus species are L. brevis and L. lindneri; less common are L. rossiae, L. buchneri, L. coryniformis, L. casei and L. backii. L. brevis often develops longer, parallel-walled, single or double rods with a round end (0.7 × 4 μm), with the double rods often being bent. It does not form cell chains, but extremely long rods (up to 50 μm) can sometimes be found in beer. Common characteristics of L. brevis are (hetero-fermentative) gas formation, fermentation of pentoses and melibioses, as well as the ability to cleave arginine. This is the most common beer spoilage bacterium, causing turbidity and sediment, while also lowering the pH perceptibly, which in turn gives beer an acidic taste. However, it does not produce diacetyl. It often appears as a secondary contaminant.

L. bucherni is able to ferment melisitose, unlike L. brevis. L. lindneri forms short, slightly irregular or coccoid cells that are arranged in longer chains. Sometimes long rods are formed. Heterofermentative species mainly ferment glucose and maltose and do not cleave arginine. Mild sedimentation and turbidity may be observed in the beer however taste defects do not usually occur. This is a typical primary contaminant that is often found in yeast factories or in the fermentation area, but can also pass through the filters, being very small cells.

L. rossiae has similar properties and is mucus-forming. Facultative heterofermentative species, such as L. casei, L. coryniformis and L. plantarum form shorter rods that are often arranged in chains. They are mostly found in weaker hop beers (e.g., wheat beer) and cause obvious taste defects due to diacetyl formation. They often appear only as secondary contaminants. The obligate homofermentative beer spoilage L. backii ferments mannose, mannitol and sorbitol. It also differentiated from the other species by the absence of fermentation of maltose and gluconate.

P. damnosus is characterized by the formation of tetrads. It is typically a primary contamination that often occurs in cultured yeast and unfiltered beer. The cells can also be transferred to the bottled beer through the filter. Contamination results in strong diacetyl formation (buttery taste) and a decrease in pH, and beers are often slightly turbid and exhibit noticeable sedimentation. Two other Pediococcus species that cause beer spoilage, P. inopinatus and P. claussenii, behave similarly, although both species are less common. The latter causes mucus formation in the beer. Enterobacteriaceae [6]

Enterobacteriaceae is a facultative anaerobic Gram-negative bacterial family. The two genera commonly associated with brewing are Citrobacter and Rahnella (most likely to be introduced with the water used for brewing). These bacteria are responsible for the production of a number of compounds causing aftertastes, such as VDKs (e.g., diacetyl), 2,3-butanediol, DMS, acetaldehyde and lactic acid. These compounds are produced at the beginning of the fermentation. Bacillus [6]

Gram-positive, facultative anaerobic, spore-forming bacteria. Due to spore formation, they survive heat treatment, including pasteurization. Bacillus also poses a risk because it can reduce nitrate to nitrite, which can lead to the formation of N-nitrosamines (classified as carcinogenic, teratogenic and mutagenic substances). Since certain Bacillus species are able to produce large amounts of lactic acid, they can also cause acidification. Most Bacillus species (but not their spores) are susceptible to the iso-alpha acids from hops. Pectinatus [6]

These Gram-negative, strictly anaerobic bacteria can produce large amounts of acetic acid and acetoin, and hydrogen sulfide production (rotten egg aroma) has also been reported.

Pectinatus cerevisiiphilus and P. frisingensis are also strictly anaerobic, catalase-negative, Gram-negative bacteria, and have similar negative effects as the species listed so far. The cells are slender (0.8 × 4 μm), parallel-walled with a pointed end, slightly bent or serpentine or corkscrew-like, and serially flagellated on one side. Similarly to M. cerevisiae, they grow in the range of 15 to 40 °C (with the optimum being between 28 and 32 °C). They ferment various sugars, sugar alcohols and organic acids (mainly pyruvate and lactate). The primary metabolites are propionic acid, acetic acid, pyruvic acid, acetoin and CO2. Beers contaminated with them (pH above 4.3, alcohol content below 5% vol.) exhibit not only serious sedimentation and turbidity problems, but also unpleasant odor and taste defects (sewage odor). Similarly to M. cerevisiae, these are typically secondary contaminants that occur primarily in the bottling area. Megasphaera

Megasphaera species can appear as Gram-negative, strictly anaerobic contaminants in both wort and finished beer. They cause turbidity in beer and produce large amounts of hydrogen sulfide and a number of short-chain fatty acids (“cheesy” aroma). [2]

Catalase-negative, strictly anaerobic, Gram-negative Megasphaera cerevisiae forms large oval or round cells (1.2 – 1.6 μm) that exist in the form of diplococci and short chains. They ferment fructose, pyruvic acid and lactic acid, in particular. [6]

The primary metabolites are butyric acid, acetic acid, propionic acid, valeric acid, as well as CO2 and hydrogen gas. Only a slight turbidity is exhibited by the beer; however, due to the above-mentioned metabolites, there can be significant odor and taste defects (sewage odor). The species is sensitive to alcohol (below 5% vol.) and prefers a higher pH value (above 4.4). The secondary contaminant that is present primarily in the vicinity of the bottling equipment are typically favorable to these bacterial species [6]. Wild yeast

Any strain of yeast, except the selected Saccharomyces yeast, is a contaminant. These yeast contaminants are usually referred to by brewers as wild yeast, which may be Saccharomyces cerevisiae or non-Saccharomyces strains, such as Brettanomyces bruxellensis, Candida or Pichia. Proliferation of wild yeast can carry a safety risk: the alcohol content can increase due to the metabolism of the infecting yeast. These wild yeasts are sometimes able to ferment dextrins and starch into ethanol (so-called superattenuation). Along with the production of ethanol, the CO2-content, and thus the bottle pressure increases, which can pose a safety risk due to the bursting of the bottles. In addition, wild yeast can ruin the beer through the production of ester or phenolic aftertaste (e.g., 4-vinylguaiacol), as well as turbidity or sediment formation. It is important to note that acid washing of the yeast cells does not remove these wild yeast contaminants [5]. Fungi

Field infestation by Fusarium fungi poses a serious food safety risk to cereals. Almost all parts of the plant (germ, root, stalk, stem, leaf pod, leaf, ear and grain) can become affected. Severely infected plants produce less and lower quality crops, toxins are produced in the diseased grains, their germination vigor is reduced. The pathogens that cause the disease are different Fusarium species with various infectivity and toxin production, which can be greatly related to environmental factors, such as temperature and humidity. The toxins can be present throughout the entire brewing process, up to the bottled finished product. Certain Aspergillus species can also produce mycotoxins. Both Fusarium and Aspergillus species produce hydrophobic compounds, which are small surfactant proteins that cause foaming [6].

4. Cleaning, disinfection

Cleaning and disinfection of the lines, tanks and equipment is key in a brewery. All surfaces and equipment must be clean, the presence of contaminating bacteria, yeasts and fungi must be eliminated.

Examples of possible contaminants in a brewery:

  • Beer left over from previous brewing
  • Microbiological contaminants (yeasts, bacteria, fungi)
  • Hop residues
  • Calcium oxalate (beer stone that can be removed with acids)
  • Lipids, proteins (removal with bases)
  • Mineral deposits in the water circuit

In this regard, it is important to distinguish between cleaning agents and disinfectants.

Cleaning agents remove product residues and deposits, such as lipids and proteins. Depending on their pH value, these cleaning agents can be classified as alkaline, acidic or neutral cleaning agents. In order to further increase the cleaning capacity, additives, e.g., surfactants can be added. These are water-soluble molecules that reduce the surface tension of water, making it easier to remove contaminants.

Disinfectants are used to destroy most microbial contaminants. Here again, it is important to point out that bacterial spores are very difficult to destroy, which is why this process is called disinfection, not sterilization. Examples of disinfectants:

  • Halogenated disinfectants, for example NaOCl (sodium hypochlorite). NaOCl is a commonly used product, but unstable above 40 °C (with increased risk of corrosion).
  • Oxidizing agents, such as H2O2.
  • Quaternary ammonium compounds (often called quats). Quats are cationic surfactants. Despite their good properties, quats are not used in breweries very often because they typically from foams and difficult to rinse, which endangers the quality of the beer, e.g., may impair the stability of the foam.
  • Steam disinfection.
  • Critical points include the so-called dead spaces (pipe ends, branches in the lines, sampling points, poor welding, etc.). Lines and tanks are best cleaned with an integrated CIP system.

5. Laboratory tests

5.1. General experience

During the microbiological testing of the sour cherry beer samples and the sour cherry concentrates, we found the following:

  • Filtering of the sour cherry beer samples was not possible due to the high fiber content.
  • Also, when testing the beers, in the case of the plate casting process, when covering 10 ml of the sample with a suitable layer thickness of 3 to 5 mm of PCA (for microbial count test) or DRBC (for yeast count test) culture medium in a large Petri dish (140 x 14.8 mm), the agar did not gel because of the low pH of the sample. Therefore, in these tests, the test volume was first reduced from 10 ml to 1 ml.
  • Then the microbiological study of the sour cherry concentrates was started, due to the expected sterility of the raw material, using our own method for the detection of presence/absence.
  • This method was further modified to include the testing of beers. As the issue was not the sterility of the beer but its practical shelf life, as a final, modified solution, the presence/absence of reproducible microorganisms was tested by an enrichment method in both cases, with the same amount of inhibitor as prescribed in the recipe of the finished beer (0.02 g/L potassium sorbate). In this way, it was practically modelled whether the microorganisms that may be present in the beer can reproduce at a high nutrient content.

5.2. Description of the test methods of sour cherry beers

5.2.1. Microbial count, plate casting, colony counting (MSZ EN ISO 4833-1:2014, accredited method)

The stock suspension and the decimal dilutions are prepared from the sample according to the international standard MSZ EN ISO 6887. Using a sterile pipette, 1 ml of the sample (for liquid samples) or stock suspension is added to two Petri dishes. The procedure is repeated with additional dilutions, if necessary. 12 to 15 ml of 44 to 47 °C PCA agar is added to each Petri dish. The Petri dishes are inverted and incubated in a thermostat at 30 °C for 72±3 hours.

5.2.2. Yeast count, surface spreading, colony counting, water activity >0.95 (MSZ EN ISO 21527-1:2013, accredited method)

The stock suspension and the decimal dilutions are prepared from the sample according to the international standard MSZ EN ISO 6887. 1 ml of the sample (for liquid samples) or stock suspension is added evenly in 3 portions to the surface of the DRBC agar filled in Petri dishes, and the sample portions are spread on the surface of the agar. The procedure is repeated with an additional degree of dilution and, if necessary, with additional dilutions. The dishes are inverted after 15 minutes and incubated in a thermostat at 25 °C for 3 to 5 days.

5.2.3. Presence/absence detection of reproducible microbes, enrichment technique (own method)

In the case of a 0.33-liter bottle of beer, the sample is divided into 3 equal portions and the sample portions are incubated for 72 hours at 30 C° in 3 x 100 ml stock broth containing 0.02 g/liter of potassium sorbate. At the end of the culture period, 1 µl of each enriched sample portion is applied to a PCA plate, and the plates are incubated for 72 hours at 30 °C. If no increase in the colonies is observed on the plate, the result is reported as ‘negative/100 ml’, while if colonies do form, the result is reported as ‘positive/100 ml’.

Composition of the PCA (Plate Count Agar) culture medium for microbial count determination:

  • tryptone 5 g/l
  • yeast extract 2.5 g/l
  • glucose 1 g/l
  • agar 9 g/l
  • pH: 7.0±0.2 (25 °C)

5.2.4. Presence/absence detection of reproducible yeast, enrichment technique (own method)

In the case of a 0.33-liter bottle of beer, the sample is divided into 3 equal portions and the sample portions are incubated for 72 hours at 25 °C in 3 x 100 ml of malt broth containing 0.02 g/liter of potassium sorbate. At the end of the culture period, 1 µl of each enriched sample portion is applied to a DRBC agar plate, and the plates are incubated for 72 hours at 25 °C. If no increase in the colonies is observed on the plate, the result is reported as ‘negative/100 ml’, while if colonies do form, the result is reported as ‘positive/100 ml’.

Composition of the DRBC (Dichloran Rose-Bengal Chloramphenicol) agar:

  • enzymatically digested animal and plant tissues 5 g/l
  • glucose 10 g/l
  • potassium dihydrogen phosphate 1 g/l
  • magnesium sulfate 0.5 g/l
  • dichloran (2,6-dichloro-4-nitroaniline) 0.002 g/l
  • Rose Bengal 0.025 g/l
  • agar 15.0 g/l
  • pH: 75.6±0.2 (25 °C)

Composition of the Takács stock broth (MSZ 3640/13-76):

  • tryptone 4 g/l
  • meat extract 4 g/l
  • yeast extract 2 g/l
  • sodium chloride 2 g/l
  • disodium hydrogen phosphate 2 g/l
  • pH 7.2-7.4 (25 °C)

Laboratory tests were carried out by the laboratory of EUROFINS Food Analytica Kft.

6. Relationships between the microbiological state of the finished product and the bottling machine

In all cases, the control tests applied during product development and subsequent production were extended to the examination of the microbiological condition of the technological equipment. At the same time, the possible effects of the microbiological condition of the equipment on product quality were explored.

In the course of the project, by examining the bottling machine, manufacturing defects of the machine were brought to light, which were later acknowledged and eliminated by the manufacturer based on the results of our tests.

  • The manufacturer’s CIP (Cleaning-In-Place) cleaning and disinfection program was set on the pneumatic branch lines of the taps with insufficient exposure time
  • The foaming water supply was not connected to the CIP system
  • The beer druck tank could not be cleaned adequately due to the dead spaces it contained
  • The CO2 inlet branch line of the beer druck tank was not connected to the CIP system

The results of the comprehensive microbiological testing of the bottling machine used in our project before conversion are summarized in Table 1, while the results of the microbiological testing of the beer bottled using this machine are summarized in Table 2. The microbiological tests were performed by the laboratory of EUROFINS Food Analytica Kft., a testing laboratory accredited by NAH (National Accreditation Authority) under reg. no. NAH-1-1582/2021. Objectionable results are highlighted in the table in red.

Table 1. Comprehensive microbiological testing of the bottling machine before conversion

Test method – yeast count: MSZ ISO 21527-1:2013 [9]
Test method – microbial count: MSZ EN ISO 4833-1:2014 [10]

Table 2. Microbiological testing of small-scale fruit beer before conversion

Test method – yeast count: MSZ ISO 21527-1:2013 [9]
Test method – microbial count: MSZ EN ISO 4833-1:2014 [10]

Prior to the conversion, the quality defects of bottled fruit beer that could be attributed to its microbiological condition were: taste defects (ester aftertaste), increase in CO2 content and thus in bottle pressure, gushing (foaming beer squirting when the bottle is opened).

At our suggestion, the following modifications were made to the bottling machine by the manufacturer:

  • Increased operating time of the CIP program on the pneumatic branch lines of the taps
  • Connection of the foaming water supply to the CIP system
  • Elimination of the dead spaces of the beer druck tank
  • Connection of the CO2 inlet line of the beer druck tank to the CIP system

The results of the comprehensive microbiological testing of the bottling machine used in our project after conversion are summarized in Table 3, while the results of the microbiological testing of the beer bottled using this machine are summarized in Table 4.

Table 3. Comprehensive microbiological testing of the bottling machine after conversion

Test method – yeast count: MSZ ISO 21527-1:2013 [9]
Test method – microbial count: MSZ EN ISO 4833-1:2014 [10]

Table 4. Microbiological testing of small-scale fruit beer after conversion

Test method – yeast count: MSZ ISO 21527-1:2013 [9]
Test method – microbial count: MSZ EN ISO 4833-1:2014 [10]

Following the conversion, the hygienic condition of the bottling machine became satisfactory (Table 3), and the previously observed quality defects of the bottled fruit beer related to its microbiological condition were eliminated, as shown by the test results in Table 4. Due to the achieved microbiological stability, the preservation of the quality of the product could be ensured.

7. References

[1] Növekedes.hu (2020): A kisüzemi sörfőzdék piaci részesedése 5-6 százalékra nőhet az új törvény hatására. (Hozzáférés: 2021. 10.16.)

[2] 2020. évi CXL. törvény a kereskedelemről szóló 2005. évi CLXIV. törvény módosításáról

[3] A Tanács 92/83/EGK Irányelve (1992. október 19.) az alkohol és az alkoholtartalmú italok jövedéki adója szerkezetének összehangolásáról. 1. szakasz, 4. cikk

[4] Ludwig Narziss (1981): A sörgyártás. Mezőgazdasági Kiadó, Budapest.

[5] KULeuvenX (2021): Beer: the science of brewing. BrewingX. KU Leuven, Leuven, Belgium

[6] Hans Michael Eßlinger (2009): Handbook of Brewing: Processes, Technology, Markets. WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

[7] Beer Judge Certification Program, Inc. (BJCP) (2015): 2015 Style Guidelines

[8] Magyar Élelmiszerkönyv Bizottság (2013): 2-702 számú irányelv (régi 2-96 számú irányelv) Sör. Magyar Élelmiszerkönyv - Codex Alimentarius Hungaricus. Magyar Élelmiszerkönyv Bizottság, Budapest

[9] MSZ ISO 21527-1:2013 Élelmiszerek és takarmányok mikrobiológiája. Horizontális módszer az élesztők és a penészek számlálására. 1. rész: Telepszámlálásos technika a 0,95-nél nagyobb vízaktivitású termékekre (Microbiology of food and animal fedding stuffs. Horizontal method for teh enumeration of yeasts and moulds. Part 1: Colony count technique in products with water activity greater than 0,95)

[10] MSZ EN ISO 4833-1:2014 Az élelmiszerlánc mikrobiológiája. Horizontális módszer a mikroorganiz-musok számlálására. 1. rész: Telepszámlálás 30 °C-on lemezöntéses módszerrel (ISO 4833-1:2013) (Microbiology of the food chain. Horizontal method for the enumeration of microorganisms. Part 1: Colony count at 30 degrees C by the pour plate technique (ISO 4833-1:2013)


Production of Single Cell Protein by the fermentation biotechnology for Animal Feeding

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Production of Single Cell Protein by the fermentation biotechnology for Animal Feeding

DOI: https://doi.org/10.52091/EVIK-2022/2-3-ENG

Received: October 2021 - Accepted: March 2022


1 Széchenyi István University, Faculty of Agricultural and Food Sciences, Department of Water and Environmental Sciences
2 SISAF Nanotechnology Drug Delivery, Ulster University
* Corresponding Author: Judit Molnár: Széchenyi István University, Faculty of Agricultural and Food Sciences, Department of Water and Environmental Sciences


Kwashiorkor, single cell protein, food by-products, animal feeding, fermentation, biotechnology

1. Summary

Background: Fermentation is a sort of biotechnology that uses microorganisms to produce animal food through chemical process. In ancient times, wastes were treated with chemicals, but now companies convert wastes to valuable food, food ingredients or feed products such as single cell oils or single cell protein. The most used substrate is molasses and corn steep liquor which is a part of the fermentation process.

Aim: The aims of the manuscript is to provide an overview of the yeast strains and food by-products used in production of single cell proteins by fermentation process. Furthermore, the manuscript summarizes the role of single cell protein in animal feed.

Methods: Electronic searches were conducted on Google Scholar database Medline and PubMed. A further search was conducted on the Food and agricultural organisation FAO research article database.

Results: Single cell protein produced by these substrates and different microorganisms (algae, yeast, bacteria) play an important role in animal feeding. Furthermore, SCP is a high-quality protein, unsaturated fatty acids, vitamins and minerals sources for animals.

Conclusion: Production of single cell of protein through the fermentation has several significant benefits including sustainability, health and production efficacy.

2. Introduction

In ancient times, wastes were treated by various chemicals, but this method wasn’t the best. As the worldwide population grows, over recent decades, both animal and dairy production have been increasing steadily. The world now produces more than 350 million tonnes of animal-derived protein, and this value will rise up to around 1250 million tonnes by 2050, to meet global demand for animal-based protein [1]. Now, a lot of company convert various wastes into useful food, food ingredients or feed products for human nutrition and animal feeding. These products are also environment friendly and healthy such as biogas, biofuels, bioenergy. Therefore, different methods and techniques are providing opportunity to develop these products as single cell oils, single cell protein, chemicals, enzymes and many others.

Following the carbohydrate and fat, protein is the major macronutrient, which the body requires in large amount. It is an essential factor for growth, repair of the body and maintenance of health. All of the proteins are made up of the 20 amino acids, and they determine the nutrition values of protein. Some of amino acids cannot be synthesized by humans but are still essential (valine, leucine, isoleucine, phenylalanine, tryptophan, lysine, histidine, methionine and threonine) and must be obtained from our diet. The general structure of amino acids is shown in the Figure 1.

Protein digestion begins in the stomach and continues in the lumen of the intestine and so the proteins are degraded into mono and di amino acids. Those amino acids are absorbed by specific transporters in the intestines, and then released into the blood for use by other tissues, that are considered as the fundamental building blocks of proteins in the body, and they serve as the nitrogenous backbones for compounds like neurotransmitters, enzymes and hormones [2, 3]. Although, both the plant and animal proteins are similar in components, both contain the nearly the same amino acids, but the animal protein contains all the essential amino acids [4].

In general, the human body needs between 1.0 g to 1.5g of protein for each kilogram of weigh in children and adults respectively [5]. If there is insufficient protein in diet chronically that could cause kwashiorkor disease, which is a severe form of malnutrition [6].

Figure 1. General formula for an amino acid: amino group (-NH2), carboxyl group (-COOH) and replaceable group (-R) [7]

Single cell protein (SCP) is one of the high qualities and valuable dietary products from wastes [8, 9, 10, 11, 12]. SCP is a biomass which is produced by different microorganisms and it can also be termed as bio-protein, microbial protein or biomass. These microorganisms can be used as protein-rich ingredients in human and animal diet as well [8]. Furthermore, the SCP can be a good alternative to plant protein sources, and it can be produced throughout the year. In addition, they don’t emit greenhouse gases. The most important thing is the selection of cheap and suitable substrates or agro-industrial by-products and valuable microorganisms to produce protein and reduce the production cost of single cell proteins [8, 13, 14, 15, 16, 17]. In order to achieve this, different substrates were used as apple pomace, yam peels, citrus pulp, potato peels, pineapple waste, papaya waste [8]. However, the most used by-products are molasses and corn steep liquor. It is also important to choose microorganisms for research and industrial purpose as well.

This manuscript focuses on single cell proteins produced by microorganisms (algae, yeast, bacteria) as an alternative protein source. Due to the favorable content values of the single cell protein produced by fermentation (protein, vitamin, mineral), it can be used in digestible form for human nutrition, especially with vitamin supplementation and this contributes to the protection and treatment of malnutrition as a functional food and functional food ingredient [10].

3. Material and method

Electronic searches were conducted on Google Scholar database, Medline and PubMed. A further search was conducted on internet. The search items included, nutrition, dietary, protein, single cell protein, immune system. This review was conducted to analyse the recent literature to show the impact of nutrition, and single cell protein on the dietary system.

4. Result

4.1. Single cell protein produced by fermentation

Single cell protein (SCP) is a protein from cultivated microbial biomass and it can be used for protein supplementation. The SCP fermentation process can be seen in Figure 2. Agricultural and industrial wastes used as substrate to yield SCP. Algae, fungi and bacteria are all the main sources of microbial protein that can be utilized as SCP (Table 1) [18]. In addition, the acceptability of species as food depends on the growth rate, substrate used, contamination, associated toxins. The produced biomass is rich in proteins, amino acids as lysine and methionine, unsaturated fatty acids, vitamins and minerals. Therefore, these are used as food, food supplements [18] and animal feed in the world.

Figure 2. Producing single cell protein by fermentation technology (Modified scheme [8])
Table 1. Single cell protein (biomass) production from microorganisms and different substrates

4.2. Use of food by-products for the production of biomass, in particular molasses and corn steep liquor

Food loss and waste reduction is an important way to reduce costs of production, increase the food system capacity and is also a way to join the environmental sustainability campaign. Food waste also contains several biodegradable components for pathogenic microorganisms that can cause communicable diseases. Thus, food loss and waste reductions also have a positive effect on the well-being and health of the consumers. Therefore, the European Union (EU) is promoting the reduction of food wastes and these food by-products from vegetables, fruits, beverages, sugar, meat, aquaculture and seafood also contain functional or bioactive components. The food by-products can be used in nutraceutical or pharmaceutical industries. These can be transformed by fermentation biotechnology into animal feed products [30]. One of the most used food by-products are molasses and corn steep liquor. Molasses (M) is a by-product of sugar cane and it contains several compounds for fermentation for example vitamins, minerals, sucrose and organic compounds. In addition, corn steep liquor (CSL) is a by-product of the corn wet milling industry and it is rich in several components such as vitamins, minerals, amino acids and proteins. Furthermore, the CSL is also an important source of nitrogen [31]. The used molasses and corn steep liquor as a substrate in the fermentation process can be seen in Table 2

Table 2. Summary of literature references of the beneficial effects of molasses and corn steep liquor

4.3. Role of single cell protein produced by fermentation in animal feeding

The high quality and high protein rich human food and animal feed important to increase with the global population grows. Single cell protein (SCP) products based on microbial biomass, have a potential ingredient to this need [42]. The SCP contains high quality omega-3 fatty acids, vitamins, micronutrients, protein and other useful component for animal body. These valuable components can be seen in Table 3.

Table 3. Valuable components in single cell protein from different microorganisms [42]

Single cell proteins in animal feed supplement protein requirements well in addition to conventional feeds. This can also affect the quality of products of animal origin. The role of single cell proteins in animal feed is confirmed by several manuscripts, which are shown in Table 4.

Table 4. The role of single cell proteins in animal feed

7. References

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[18] Anupama, Ravindra P. (2000): Value-added food: Single cell protein. Biotechnology Advances.18. pp. 459-479. DOI

[19] Patelski P., Berlowska J., Dziugan P., Pielechprzybylska K., Balcerek M., Dziekonska U., Kalinowska H. (2015): Utilisation of sugar beet bagasse for the biosynthesis of yeast SCP. Journal of Food Engineering. 167. pp. 32-37. DOI

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[22] Coca M., Barrocal V. M., Lucas S., Gonzálezbenito G., García-Cubero M. T. (2015): Protein production in Spirulina platensis biomass using beet vinasse-supplemented culture media. Food and Bioproducts Processing. 94. pp. 306-312. DOI

[23] Hanh V., Kim K. (2009): High-Cell-Density Fed-Batch Culture of Saccharomyces cerevisiae KV-25 Using Molasses and Corn Steep Liquor. Journal of Microbiology and biotechnology.19. pp. 1603-1611. DOI: DOI

[24] Zepka L. Q., Jacob-Lopes E., Goldbeck R., Souzasoares L. A., Queiroz M. I. (2010): Nutritional evaluation of single-cell protein produced by Aphanothece microscopica Nägeli. Bioresource Technology. 101. pp. 7107-7111. DOI: DOI

[25] Rajoka M. I., Khan S. H., Jabbar M. A., Awan M. S., Hashmi A. S. (2006): Kinetics of batch single cell protein production from rice polishings with Candida utilis in continuously aerated tank reactors. Bioresource Technology. 97. pp. 1934-1941. DOI: DOI

[26] Yadav J. S. S., Bezawada J., Ajila C. M., Yan S., Tyagi R. D., Surampalli R. Y. (2014): Mixed culture of Kluyveromyces marxianus and Candida krusei for single-cell protein production and organic load removal from whey. Bioresource Technology. 164. pp. 119-127. DOI

[27] De Gregorio, A., Mandalari, G., Arena, N., Nucita, F., Tripodo, M. M., Lo Curto, R. B. (2002): SCP and crude pectinase production by slurry-state fermentation of lemon pulps. Bioresource Technology. 83. pp. 89-94. DOI

[28] Lo Curto, R. B., Tripodo M. M. (2001): Yeast production from virgin grape marc. Bioresource Technology. 78. pp. 5-9. DOI

[29] Fontana J. D., Czeczuga B., Bonfim T. M. B., Chociai M. B., Oliveira B. H., Guimaraes M. F., Baron M. (1996): Bioproduction of carotenoids: the comparative use of raw sugarcane juice and depolymerized bagasse by Phaffia Rhodozyma. Bioresource Technology. 58. pp. 121-125. DOI

[30] Socas-Rodríguez B., Álvarez-Rivera G., Valdés A., Ibánez E. (2021): Food by-products and food wastes: are they safe enough for their valorization? Trends in Food Science & Technology. 114. pp. 133-147. DOI

[31] Amado I. R., Vázquez J. A., Pastrana L., Teixeira J. A. (2017): Microbial production of hyaluronic acid from agro-industrial by-products: Molasses and corn steep liquor. Biochemical Engineering Journal. 117. pp. 181-187. DOI

[32] Palmonari A., Cavallini D., Sniffen C. J., Fernandes L., Holder P., Fagioli L., Fusaro I., Biagi G., Formigoni A., Mammi L. (2020): Short communication: Characterization of molasses chemical composition. Journal of Dairy Science. 103. pp. 6244-6249. DOI

[33] Wang J., Chen L., Yuan X.-J., Guo G., Li J.-F., Bai Y.-F., Shao T. (2017): Effects of molasses on the fermentation characteristics of mixed silage prepared with rice straw, local vegetable by-products and alfalfa in Southeast China. Journal of Integrative Agriculture. 16. pp. 664-670. DOI

[34] Sarka E., Bubnik Z., Hinkova A., Gebler J., Kadlec P. (2012): Molasses as a by-product of sugar crystallization and a perspective raw material. Procedia Engineering. 42. pp. 1219-1228. DOI

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[36] Siverson A., Vargas-Rodriguez C. F., Bradford B. J. (2014): Short communication: Effects of molasses products on productivity and milk fatty acid profile of cows fed diets high in dried distillers grains with solubles. Journal of dairy Science. 97. pp. 3860-3865. DOI

[37] Karigidi K. O., Olaiya C. O. (2020): Antidiabetic activity of corn steep liquor extract of Curculigo pilosa and its solvent fractions in streptozotocin-induced diabetic rats. Journal of Traditional and Complementery Medicine. 10. pp. 555-564. DOI

[38] Li X., Xu W., Yang J., Zhao H., Xin H., Zhang Y. (2016): Effect of different levels of corn steep liquor addition on fermentation characteristics and aerobic stability of fresh rice straw silage. Animal Nutrition. 2. pp. 345-350. DOI

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Application of an in vitro test system for the selection of probiotic bacterial strains

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Application of an in vitro test system for the selection of probiotic bacterial strains

DOI: https://doi.org/10.52091/EVIK-2022/2-4-ENG

Received: March 2022 - Accepted: May 2022


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


probiotic, Lactobacillus, bile acid, gastric acid, RAPD-PCR, autoaggregation

1. Summary

The aim of our studies was to evaluate in vitro methods for the simple and efficient selection of putative probiotic bacterial strains. Of the possible methods, the following were tested: culturing on selective media, Gram staining, catalase assay, hemolytic, clonality and aggregation ability, gastric acid tolerance and bile acid tolerance. A total of 217 bacterial strains isolated from raw sheep’s milk, curdled milk and sheep’s cheese samples produced in Transylvania were included in our experiments. Isolates with hemolytic activity, as well as those exhibiting Gram-negative or catalase-positive phenotypes not characteristic of probiotics were excluded from our studies. Based on the results of RAPD-PCR studies suitable for the detection of individual-level polymorphisms, a total of 34 clone classes and 57 strains with unique RAPD patterns were identified. From each of the 34 clone classes thus narrowed, one strain was selected and tested for its aggregation ability, as well as its gastric acid and bile acid tolerance. High aggregation values above 70%, typical of probiotic strains, were measured in the case of a total of six isolates. In the course of the presence-absence studies conducted on the surface of solid media supplemented with acid or bile acid, it was possible to select several strains specifically tolerant to acid or bile acid. Based on our results, isolates to be included in further tests, e.g., in antibiotic resistance and antimicrobial activity assays, were selected.

2. Bevezetés

Probiotics are living organisms that, when used in appropriate amounts, have a beneficial effect on the health of the host organism [1, 2]. They must meet a number of conditions in order to be allowed to display the probiotic designation. Among other things, they need to have an increased tolerance to various body fluids (gastric acid, bile acids, digestive enzymes) and they must stabilize the intestinal microbiota by binding to intestinal epithelial cells through their ability to adhere [3].

There is a growing worldwide demand for probiotic products that have a beneficial effect on health, both in terms of human consumption and the feeding of farm animals. The use of antibiotics for yield enhancement has been banned in the European Union since 2006 [4], and the focus has been even more on probiotics since that date.

Year after year, a large number of bacterial strains are isolated in order to exploit their beneficial effects on health. Complex and costly animal studies must be preceded by a selection system of in vitro experiments that allows the simple, rapid and cost-effective selection of strains, from hundreds or even thousands of isolates, that will hopefully prove probiotic in in vivo studies [5, 6, 7].

Based on the above, the aim of our work was to develop and evaluate in vitro measurement methods that can be used to quickly and efficiently investigate the classical microbiological characteristics, clonality, aggregation ability, as well as the resistance to gastric acid and bile acid of bacterial strains. We sought to answer the question whether the large number of isolates studied by us included clones and strains with potentially beneficial (even probiotic) properties that should be included in further in vitro studies. It was also examined whether the test system was working well or whether it was necessary to optimize the individual steps, as well as what acid and bile acid concentrations the different strains were able to tolerate, and whether there was any correlation between the results of the aggregation test and the acid and bile acid tolerance. Accordingly, of the in vitro tests, the results obtained by the following test methods are presented in our publication:

  • Classical microbiological tests (culturing on selective media and determination of colony morphology, Gram staining and subsequent microscopic examination, catalase test, hemolysis test)
  • Clonality assay by RAPD-PCR method
  • Autoaggregation test
  • Presence-absence studies conducted on the surface of solid media supplemented with acid or bile acid

3. Materials and methods

3.1 Isolation, culturing, preservation and storage of bacterial strains

Our studies were conducted with bacterial strains isolated from raw sheep’s milk, curdled milk and sheep’s cheese samples produced in Transylvania. The products had a natural microbiota and no commercially available starter cultures were used for their production. For the preparation of the cheeses, rennet was made by the shepherds from veal stomachs. The goal was to isolate highly efficient probiotic strains that would be later used in the development of probiotic products. Restoration and culturing of the 217 isolates and the control strains were performed under the conditions listed in Table 1.

Restoration and culturing conditions of the isolated and control bacterial strains included in the experiments

* De Man–Rogosa–Sharpe agar supplemented with clindamycin and ciprofloxacin

Isolates were preserved and stored in glycerol stock solutions. A strain taken from the surface of MRS–CC agar or MRS pH 5.4 agar was washed into 3 ml of broth with an inoculating loop, and then it was incubated according to the needs of the strain. 300 µl of the grown culture was added to a cryo (freezer) tube, 900 µl of a 60% glycerol solution was added, it was vortexed and frozen in liquid nitrogen for ca. 30 seconds. Storage was conducted at -80 °C in an ultra-freezer.

3.2. Selective culture conditions, its media and their preparation

3.2.1. Physiological saline solution

For the preparation of the diluent used to prepare the decimal dilution series, 8.5 g of NaCl and 1 g of tryptone were weighed and dissolved in 1 L of distilled water. 9.3 ml was added to the test tubes, and they were sterilized in an autoclave at 121 °C for 15 minutes.

3.2.2. Phosphate buffer solution (PBS)

For one liter of distilled water, the following substances were weighed on an analytical balance: 80 g of sodium chloride, 2 g of potassium chloride, 14.4 g of disodium hydrogen phosphate dodecahydrate and 2.4 g of potassium dihydrogen phosphate. Dissolution was aided by a magnetic stirrer and when the solution became particle-free, it was sterilized in an autoclave at, 121 °C for 15 minutes. The solution thus prepared corresponds to PBS with a tenfold concentration, i.e., for further use it has to be diluted as follows: 100 ml of 10× PBS solution is added to 900 ml of distilled water. After proper mixing, the 1× PBS solution is ready for use.

3.2.3. De Man–Rogosa–Sharpe (MRS) agar and broth (pH = 6.2)

Of commercially available MRS broth (VWR, Radnor, PA, USA) or MRS agar (VWR), the quantity recommended by the manufacturer was weighed to analytical accuracy and ten dissolved in distilled water, using a magnetic stirred until dissolved. The pH was adjusted to the desired value (6.2 ± 0.2) with 1 M HCl. Following this, the culture media were sterilized in an autoclave at 121 °C for 15 minutes.

3.2.4. MRS agar (pH = 5.4)

MRS agar (VWR) was prepared according to the manufacturer’s instructions, its pH value was adjusted to 5.4 with 1 M HCl, and then it was sterilized in an autoclave under standard conditions (121 °C, 15 minutes).

3.2.5. MRS agar supplemented with clindamycin and ciprofloxacin (MRS–CC)

In addition to the basic MRS agar, MRS–CC agar also contained two antibiotic stock solutions that could not be sterilized in an autoclave. For the preparation of one of the stock solutions, 2.0 mg of clindamycin hydrochloride (Sigma Aldrich, St. Louis, MO, USA) was dissolved in 10 ml of distilled water, while for the other, 20.0 mg of ciprofloxacin hydrochloride (Sigma Aldrich) was dissolved in 10 ml of distilled water. The antibiotic stock solutions were then filtered through a 0.22 μm pore size membrane filter (Millipore, Burlington, MA, USA) into sterile screw-capped Erlenmeyer flasks. 0.1 ml of clindamycin and 1.0 ml of ciprofloxacin stock solutions were added to the MRS agar cooled to 45 °C under aseptic conditions, using sterile, disposable pipettes (Greiner Bio-One Hungary, Mosonmagyaróvár, Hungary). Thus, the final concentration of clindamycin in the basic MRS agar was 0.1 mg/l, while that of ciprofloxacin was 10.0 mg/l.

3.2.6. CASO agar

CASO agar (VWR) and CASO broth (VWR) were prepared according to the manufacturer’s instructions. Sterilization was performed in an autoclave under standard conditions, at 121 °C for 15 minutes.

3.2.7. Anaerobic culturing

Anaerobic conditions in the course of our studies were ensured as follows: agar plates were incubated in an AnaeroPack Rectangular jar (Merck, Darmstadt, Germany), with the addition of GENbox anaer anaerobic salt (bioMériux, Marcy-l’Étoile, France). Information on the existence of anaerobic conditions was provided by the color change of the Microbiologic Aerotest indicator (Merck) from white to blue.

3.3. Classical microbiological tests

3.3.1. Examination of colony morphology

Macromorphological characteristics of the restored strains were recorded. Among other things, the size, color, surface properties (glossy, matte) of the colonies, as well as the design of the edges of the colonies (regular, irregular, jagged) were observed.

3.3.2. Gram staining

One drop of distilled water, in which a solitary colony was suspended, was added to a degreased slide. The dried smear was stained with crystal violet solution for 2 minutes, then it was treated with lugol solution for 1 minute. Following this, the sample was rinsed with distilled water, then treated with a decolorizing solution for half a minute, which extracted the dye from the Gram-negative cells but not the Gram-positive ones. After another rinsing with distilled water, contrast staining was carried out with safranin for 1 minute. This was followed by rinsing with distilled water, the smears were allowed to dry, and then they were examined under a light microscope (Axio Scope, Carl Zeiss, Oberkochen, Germany) at various magnifications. Performing Gram staining is important because lactic acid bacterial strains with potential probiotic properties are among Gram-positive microbes.

3.3.3. Catalase test

There are microorganisms that produce catalase enzymes that can break down toxic hydrogen peroxide into water and oxygen (2 H2O2 = 2 H2O + O2). In order to confirm the catalase production of our isolates, colonies of fresh cultures were placed on slides using an inoculation loop, and a drop of 3% H2O2 was added. In positive cases, colonies began to visibly bubble. S. aureus strain ATCC 49775 was used as a positive control, which indicated catalase activity with strong effervescence. Catalase-positive strains are not suitable as probiotics for sure.

3.3.4. Hemolysis test

In the coarse of our hemolysis studies, one colony of each freshly restored strain was transferred to Columbia blood agar (Biolab Zrt., Budapest, Hungary). Results were evaluated after 24 hours of anaerobic incubation at 37 °C. S. aureus, which exhibits β-hemolysis on 5% sheep blood culture medium, was again used as a positive control.

3.4. Clonality test

Bacterial DNA was isolated from the bacterial strains using Chelex 100 Resin (Bio-Rad, Hercules, CA, USA), according to the protocol provided by the manufacturer. For the polymerase chain reaction, the reaction mixture containing the Red Taq 2 mM MgCl2 Master Mixet (VWR), the primer named 1254 chosen by us (Bio-Science, Budapest, Hungary), molecular biology grade AccuGENE water (Lonza, Basel, Switzerland) and the sample (DNA template of the bacterial strains) were measured into a 1.5 ml Eppendorf tube. The samples were analyzed by RAPD-PCR, using the RAPD_03 program of a Mastercycler PCR (Eppendorf, Hamburg, Germany) instrument, the parameters of which are shown in Table 2.

Table 2. Parameters of the RAPD-PCR method

Steps 2 through 4 were carried out 40 times. Following the completion of the program, the amplified DNA molecules were made visible and evaluated by gel electrophoresis. A 1% agarose gel was prepared for the gel electrophoresis. 0.6 g of agarose (VWR) was weighed and dissolved in 60 ml of 1×TBE TRIS-boroacetic acid solution. The solution was boiled until completely homogenized. It was cooled to lukewarm temperature and 6 µl of DNS ECO Safe dye solution (Pacific Image Electronics, Torrance, CA, USA) was added. Meanwhile, it was agitated on a magnetic stirrer, and then the gel was poured. The cooled gel with the dye was poured into the tray. After setting, the tray was placed in the electrophoresis tank, previously filled with gel electrophoresis buffer (1×TBE solution), then the gel comb was removed. The RAPD-PCR reaction products were then added to the individual pockets.

3.5. Investigation of autoaggregation

The test method used was based on the research of Del Re et al. [8], with minor modifications. Our own isolates and control strains were incubated at 37 °C for 18 hours under anaerobic conditions in MRS broth at pH 6.2. The samples were then centrifuged (Eppendorf Centrifuge 5804 R) at 2426 × g for 6 minutes.

The supernatant was discarded, 50 ml of 1×PBS solution was measured onto the bacterial pellets, and they were vortexed (10 sec). They were centrifuged again the supernatant was discarded and the pellet was redissolved in 1×PBS solution. After vortexing, 900 µl of 1×PBS and 100 µl of cell suspension were measured into semi-micro cuvettes (Greiner Bio-One Hungary). Optical density was measured at a wavelength of 600 nm with a BioMate 160 UV-VIS spectrophotometer (Thermo Fisher Scientific; Waltham, MA, USA), and the OD600 values were standardized to 0.2 for each sample for the measurement results to be comparable. The set values were checked by OD600 measurements. In the case of appropriate values, 4 ml each of bacterial suspension was dispensed into sterile Wassermann tubes, labeled A, B and C for each sample, to ensure three technical replicates. The samples thus prepared were aerobically incubated in Wassermann tubes at room temperature during the assay. Optical density measurements were performed at 0, 5 and 24 hours. At each measurement time point, 200 µl was removed from the top of the bacterial suspension with a wide-tip pipette tip (Axygen, Union City, CA, USA), and it was diluted with 800 µl of 1×PBS solution in a semi-micro cuvette. At each of the three measurement times, the OD600 value of each lettered sample was measured three times and the percentage of aggregation was calculated according to the formula given by García-Cayuela et al. [9]

[1 − (Ameasurement time / A0) × 100],

where: Ameasurement time: the absorbance value of the cell suspension at the given measurement time (5 h, 24 h); A0: the absorbance value of the cell suspension at time 0 h.

Currently, there is no uniform system for the assessment of autoaggregation. In the course of their studies, Del Re et al. [8] rated strains with an aggregation value of >80% as well aggregating isolates, while strains with a value of <10% were considered non-aggregating.

3.6. Analysis of acid and bile acid tolerance

3.6.1. Acid and bile acid culture media required for the test

To test for acid tolerance, MRS culture medium (VWR) was prepared as described, and it was sterilized in an autoclave at 121 °C for 15 minutes. Next, the pH was adjusted with 1 M HCl under aseptic conditions to the following values: 6.0; 5.5; 5.0; 4.0; 3.0. The sterile culture media were cooled back to 45 °C, and plates were poured into square Petri dishes (Greiner Bio-One Hungary). The MRS culture medium with a pH of 6.0 served as the untreated medium.

Too test for bile acid tolerance, the MRS culture medium (VWR) was prepared according to the manufacturer’s instructions. After sterilization (at 121 °C, 15 min), sterile-filtered porcine bile (Sigma Aldrich) was added to the basic agar cooled back to 45 °C, using a 0.45 μm pore size membrane filter (Thermo Fisher Scientific). Supplementation was performed to achieve final bile concentrations of 0%, 0.1%, 0.2% and 0.5% in the culture medium. MRS agar containing no bile served as a negative control.

3.6.2. Strain restoration and optical density (OD) measurement

Bacterial strains were restored in a pH 6.2 MRS broth as a result of anaerobic incubation at 37 °C for 18 hours. The multiplied cultures formed more or less pellets at the bottom of the Falcon tube, which was evaluated. The cultures were centrifuged (2426 × g, 6 min, room temperature) (Eppendorf Centrifuge 5804 R). The supernatant was discarded, and the samples were redissolved in 1×PBS solution. After a short (10 sec) vortexing, centrifugation was repeated, and the supernatant was discarded again. After redissolution in 1×PBS solution, vortexing was performed for 10 sec, and the optical density of a 10-fold dilution of the suspension was measured with a BioMate 160 UV-VIS spectrophotometer (Thermo Fisher Scientific) at 600 nm. Following the measurement, suspensions with a uniform OD600 value of 0.5 were prepared. For accuracy, the OD600 values of the suspensions with adjusted cell densities were remeasured.

3.6.3. Presence-absence test

Of the cell suspensions with an OD600 = 0.5, 18 (9 technical × 2 biological replicates) × 10 µl were applied to the surface of culture media with different pH values and bile acid contents, and then the plates were incubated at 37 °C for 48 hours, as described in Section 3.2.7.

3.6.4. Process of bile acid and hydrochloric acid treatment

The tested bacterial strains were treated with bile acid and hydrochloric acid, according to the agents added to the culture media. MRS culture media with a pH of 6.0 with no bile or hydrochloric acid served as negative controls. The procedure of the tests is illustrated in Figure 1.

Figure 1. Flow chart of bile acid and hydrochloric acid treatment

3.6.5. Inoculation and viable cell count determination

Decimal dilution series were prepared from the cultures of both our own isolates and the control bacterial strains, and then 100 µl of each dilution member was spread on the surface of MRS agar plates with a pH value of 6.0. The plates thus prepared were incubated at 37 °C for 72 hours under anaerobic conditions. At the end of the incubation period, the colonies were counted.

4. Results and evaluation

4.1. Classical microbiological tests

The aim of classical microbiological tests was to select Gram-negative, catalase-positive and hemolyzing strains. Using these methods, we were able to eliminate out of the 217 isolates those that did not meet the criteria for probiotics. Table 3 shows a non-exhaustive list of strains with appropriate characteristics based on the results of classical microbiological tests, which were included in subsequent studies (aggregation, acid tolerance and bile acid tolerance studies).

Table 3. Main characteristics of strains based on the results of classical microbiological tests

*Colony morphology was examined with strains developed on MRS agar adjusted to a pH value of 6.2.

Of the 217 isolates, 25 catalase-positive and 29 Gram-negative strains were identified. These were also excluded from the clone classes and from individual strains that did not fit into the clone classes after the clonality test. None of the strains hemolyzed on blood agar, so although this test did not help to narrow down the large sample number, it was absolutely necessary to perform it to assess the safety of the probiotic strains.

According to the practice of our group, Sedlačková et al. Also included only Gram-positive, rod-shaped and catalase-negative isolates in their further in vitro studies [10]. In their study, a total of 59 Gram-positive and catalase-negative strains were isolated, of which 7 were isolated from raw milk and 12 from cheese prepared from raw cow’s milk. The colony morphology was found to be similar to that of the colonies of L. acidophilus LA-5.

4.2. Clonality test

RAPD-PCR assays were carried out in parallel with classical microbiological tests. Based on the unique RAPD patterns, the 217 strains were classified into 34 clone classes, of which a gel photograph of clone class 34 is shown in Figure 2; Figure 3 shows several clone classes and individual strains.

Figure 2. Clonality test of members of clone class 34 (samples: E211–E217, positive control: Lactobacillus acidophilus LA-5, negative control: distilled water, molecular marker: WM; Gene Ruler 1 kb Plus DNA Ladder)
Figure 3. Gel photograph of several clone classes and individual strains (samples: E149–E194, positive control: E31, negative control: distilled water, molecular marker: WM; Gene Ruler 1 kb Plus DNA Ladder)

In the course of our studies, 57 individual strains were found, which could not be classified into clone classes, so the range of isolates was narrowed down to 91 based on the results of the clonality tests. Gram-negative and catalase-positive isolates were excluded by classical microbiological methods, leaving a total of 34 clone classes and 37 individual strains that could not be classified into clone classes, reducing the starting number to 71 isolates. This greatly aided preselection, as less than one third (32.7%) of the strains remained. As the results of the RAPD-PCR assays are highly dependent on laboratory conditions, precise execution of the method is of paramount importance for the reproducibility of the results [11]. The 1254 primer used allowed the comparison of isolates with similar patterns in the course of the RAPD-PCR assays. This is consistent with the statement of Torriani et al. [12] that primer 1254 is eminently suitable for detecting polymorphisms among L. delbrueckii strains.

4.3. Examination of autoaggregation

In our further studies, the 37 individual strains that could not be classified into clone classes were not included, so the in vitro test series were continued by selecting one bacterial strain from each of the 34 clone classes for the examination of autoaggregation. Our goal was to find well-aggregating (>70% after 5 hours of incubation, >80% after 24 hours of incubation) and non-aggregating (<25%) strains, which then could be included in further acid and bile acid tolerance experiments. It was hypothesized that well-aggregating strains would be more likely to be probiotic, and thus they may also be able to better tolerate acid and bile acid treatment.

Aggregation assay measurements were carried out after 0, 5 and 24 hours. It was decided to perform measurements after 5 hours on the basis of the results of Kos et al. [13], who found that L. acidophilus M92 was already highly autoaggregated after 5 hours. The authors cultured their test strains in MRS broth to preserve some of the cell surface proteins that allow aggregation [13].

The 34 strains were tested in two biological duplicates. Isolates with an aggregation value over 70% were found after 5 hours of treatment, namely the following six E15, E66, E92, E173, E198 and E216. L. acidophilus LA-5 and ATCC 4356 strains used as positive controls also aggregated well (78.2% and 72.1%, respectively) (Figure 4).

It should be mentioned that the well-aggregating strains formed pellets visible to the naked eye at the bottom of the Wassermann tubes, and the upper part of the suspension became clear. The same finding was made by García-Cayuela et al. [9], who isolated 126 L. plantarum strains from cheese samples made from raw milk and carried out preliminary evaluation of the aggregation (sedimentation) ability of the strains in MRS broth with the naked eye, on the basis of which the appearance of snowflake-like aggregates has been reported. Fourteen strains were included in the autoaggregation study, and optical density measurements were performed after 2, 6, 20 and 24 hours. The highest autoaggregation values (28.5-59.5%) were observed after 1 day. Values increased over time, however, they varied from strain to strain. Compared to the aggregation percentages reported by them, we measured higher values (>75%) after 5 hours of incubation.

Xu et al. [14] tested the ability of probiotic and pathogenic strains to self-aggregate. The results obtained after 2 hours of incubation showed that three strains (Bifidobacterium longum B6, L. rhamnosus GG and L. brevis KACC 10553) performed well, with aggregation percentages between 40 and 50%. Tuo et al. [15] examined the aggregation ability of 22 Lactobacillus strains after 5 hours of incubation at 37 °C, and values of 24.2 to 41.4% were obtained. They used L. rhamnosus GG as a positive control, which proved to be the best performing strain with an aggregation value of 41.4%.

Cumulative results of the autoaggregation study of Transylvanian and control strains (after 5 and 24 hours of incubation) are shown in Figure 5. It can be stated that each strain achieved a higher value after 24 hours compared to its result after 5 hours. The probiotic L. acidophilus LA-5 used as a control and L. acidophilus ATCC 4356, which has a well-aggregating phenotype, performed excellently after 24 hours, as reported in the literature (94.1% and 93.5%, respectively). Of the strains belonging to the 34 clone classes, 19 aggregated above 80%. This means that the method developed by us proved to be suitable to distinguish between well and poorly aggregating isolates. In a 24-hour autoaggregation study of Lactobacillus strains isolated from yogurts, Prabhurajeshwar and Chandrakanth [16] measured values that were lower than our results (39.4-52.0%).

Figure 4. Results of autoaggregation studies of our own isolates and control strains after 5 hours of incubation [Data represent mean ± standard deviation of 2 biological x 3 technical replicates; the horizontal red line allows the visualization of well-aggregating (>70%) strains]
Figure 5. Results of autoaggregation studies of our own isolates and control strains after 5 and 24 hours of incubation [Data represent mean ± standard deviation of 2 biological x 3 technical replicates; the horizontal red line allows the visualization of well-aggregating (>80%) strains ]

4.4. Examination of acid and bile acid tolerancea

Acid and bile acid tolerance was studied using 6 strains (E15, E66, E92, E173, E198, E216) that aggregated well after 5 hours of incubation, and L. acidophilus LA-5 was used as a positive control, the latter strain being probiotic, having adequate aggregation indices and having displayed excellent properties in similar studies in the past [17]. In addition, from our own isolates, strain E10 with less favorable aggregation ability (22.7%) was also included in our studies in order to determine whether there is a correlation between good aggregation and between acid and bile acid tolerance.

Results were recorded after 48 hours of incubation. At the site of the bacterial suspension droplets with a volume of 10 µL inoculated onto the surface of the culture medium, colony growth or the absence of proliferation was observed. It was judged with the naked eye whether the strains were able to visibly proliferate on the surface of the culture media supplemented with acid or bile acid, as well as on the surface of the control culture media (presence-absence test). On the one hand, we were looking to answer the question what acid and bile acid concentrations the individual strains were able to tolerate and, on the other hand, whether there is a correlation between the aggregating ability and the acid or bile acid tolerance. Our results are shown in Tables 4 and 5.

Table 4. Results of the presence-absence test performed on the surface of solid culture medium supplemented with acid*

* n = 18 (9 parallels × 2 replicates).
0: no proliferation, +: poor proliferation, ++: moderate proliferation, +++: clearly visible, strong proliferation.

Table 5. Results of the presence-absence test performed on the surface of solid culture medium supplemented with bile acid*

* n = 18 (9 párhuzamos × 2 ismétlés).
0: nincs szaporodás, +: gyenge szaporodás, ++: közepes mértékű szaporodás, +++: jól látható, erőteljes szaporodás.

It can be seen that L. acidophilus LA-5 grew well on MRS culture media with pH values of 6.0, 5.5, 5.0 and 4.0, as well as on MRS culture media containing 0.1% and 0.2% bile acid, thus it proved to be well tolerant of acid and moderately tolerant of bile acid. The control strain showed only a week growth on culture media containing 0.5% bile acid. Neither the control, nor the Transylvanian strains formed colonies on the most acidic (pH = 3.0) MRS culture medium, so solid culture media with pH values of 4.0 and 3.0 proved to be suitable for pre-selection.

Pan et al. [18] maintained a L. acidophilus NIT strain isolated from infant feces in a glycine–hydrochloric acid buffer (pH: 2.0; 3.0; 4.0) for 1, 2 or 3 hours. After the treatment, the bacterial pellet was resuspended, and 20 µL of the suspension of the appropriate dilution members was spread on the surface of MRS agar plates. It was found that after 3 hours of treatment, only 10% of L. acidophilus cells survived. Although our studies were not performed in the same experimental setup, the results may explain why L. acidophilus did not form colonies on a culture medium with a pH value of 3.0. By the addition of 3% whey protein isolate, Vargas et al. [19] achieved that Streptococcus thermophilus ST-M5 and L. delbrueckii subsp. bulgaricus LB-12 survived acid treatment in maximum numbers. The aim of Valente et al. [20] was to assess the in vitro and in vivo probiotic potential of lactic acid bacterial strains (L. plantarum B7 and L. rhamnosus D1) isolated from traditional Brazilian cheeses. Both strains were moderately tolerant of 0.3% of ox bile after 12 hours of incubation. Both isolates B7 and D1 have been shown to be resistant to artificial digestive juices (pH: 2.0 and 3 g/L pepsin) [20].

The physiological concentration of bile acid salts varies between 0.3% and 0.5% in the gastrointestinal tract [21], this is why 0.5% was chosen as the highest bile concentration. The author mentioned also added to his culture medium 0.3, 0.5, 1.0 or 2.0% bile acid salt, and then 10 µL of the stock culture was applied to the surface of the culture medium. Although he worked not with Lactobacillus, but with Lactococcus strains isolated from raw cow’s and goat’s milk and from traditional kefir, his experimental system was similar to ours. Lactococcus lactis strains did not tolerate any of the bile acid concentrations used.

Based on our results, it was found that the selected isolates generally well tolerated the presence of 0.5% bile acid, which in turn was not true for strain E10, which barely proliferated even at the lowest (0.1%) bile concentration. The poor aggregation ability of isolate E10 was accompanied by good acid tolerance and poor bile acid tolerance. The control strain L. acidophilus LA-5, although poorly, but still proliferated on the culture medium containing 0.5% bile. During the procedure used, the strains were exposed to the destructive ingredients not only for a few hours, but they were in contact with them for 48 hours. It is worth mentioning that the negative effects of the destructive agents can be mitigated by the addition of whey protein powder to the culture medium [19]. Presence-absence testing on the surface of the solid culture medium supplemented with acid or bile acid can be considered a relatively fast method, because the required culture media can be prepared easily, dropping onto the surface of the culture medium can be performed quickly, so the results are available in a short time.

5. Conclusions

Our efforts to develop some elements of an in vitro test system for the selection of probiotic bacterial strains have proven to be successful. The steps presented here do not necessarily need to be further refined, because they are already capable of the pre-selection of large sets of isolates. Although primer 1254 has been shown to be a good choice, it will be worth performing the RAPD-PCR reaction with other primers in subsequent clonality assays. There was a positive correlation between the results of the aggregation studies and those of the acid and bile acid tolerance tests, however, to factually establish the probiotic properties of the isolated strains, further in vitro studies and in vivo animal experiments are needed. In order to have an even more efficient selection than at present, it seems worthwhile to supplement the test system with other elements, e.g., antibiotic resistance or antimicrobial activity assays.

6. Acknowledgment

The authors would like to thank the financial support of the project titled “Innovative scientific workshops in Hungarian agricultural higher education”, ID no. EFOP-3.6.3-VEKOP-16-2017-00008, and of the project titled “Developments for intelligent specialization in cooperation between the University of Veterinary Medicine and the Faculty of Agricultural and Food Sciences of Széchenyi István University”, ID no. EFOP-3.6.1-16-2016-00024.

7. Literature

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[5] Papadimitriou, K., Zoumpopoulou, G., Foligné, B., Alexandraki, V., Kazou, M., Pot, B., Tsakalidou, E. (2015): Discovering probiotic microorganisms: in vitro, in vivo, genetic and omics approaches. Frontiers in Microbiology 6 pp. 58. DOI

[6] Williams, C.F., Walton, G.E., Jiang, L., Plummer, S., Garaiova, I., Gibson, G.R. (2015): Comparative analysis of intestinal tract models. Annual Review of Food Science and Technology 6 pp. 329-350. DOI

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[10] Sedláčková, P., Horáčková, Š., Shi, T., Kosová, M., Plocková, M. (2015): Two different methods for screening of bile salt hydrolase activity in Lactobacillus strains. Czech Journal of Food Sciences 33 pp. 13-18. DOI

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[12] Torriani, S., Zapparoli, G., Dellaglio, F. (1999): Use of PCR-based methods for rapid differentiation of Lactobacillus delbrueckii subsp. bulgaricus and L. delbrueckii subsp. lactis. Applied and Environmental Microbiology 65 pp. 4351-4356. DOI

[13] Kos, B., Šušković, J., Vuković, S., Šimpraga, M., Frece, J., Matošić, S. (2003): Adhesion and aggregation ability of probiotic strain Lactobacillus acidophilus M92. Journal of Applied Microbiology 94 pp. 981-987. DOI

[14] Xu, H., Jeong, H.S., Lee, H.Y., Ahn, J. (2009): Assessment of cell surface properties and adhesion potential of selected probiotic strains. Letters in Applied Microbiology 49 pp. 434-442. DOI

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[19] Vargas, L.A., Olson, D.W., Aryana, K.J. (2015): Whey protein isolate improves acid and bile tolerances of Streptococcus thermophilus ST-M5 and Lactobacillus delbrueckii ssp. bulgaricus LB-12. Journal of Dairy Science 98 pp. 2215-2221. DOI

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Effect of a compound bio-preservative on microbiological indicators and shelf life of fresh pork chops

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Effect of a compound bio-preservative on microbiological indicators and shelf life of fresh pork chops

DOI: https://doi.org/10.52091/EVIK-2022/2-5-ENG

Received: December 2021 – Accepted: March 2022


1 South Ural State University
2 South Ural State Agrarian University
3 LLC "Antey"


preservative, antioxidant, fresh meat products, total viable count, yeast, shelf life, storage, microbiology

1. Summary

The article deals with the study of the effect that a compound preservative produces on microbiological indicators and shelf life of fresh pork products. The effect of various preservatives on the total viable count and yeast growth in fresh meat during storage was studied. Experimental studies have shown that the compounds of additive a preservative mixture* actively inhibits microorganism growth during the fresh pork chops storage. In the control sample, the number of microorganisms on the seventh day of storage was 12*104 CFU/g, and, in the sample with the compound additive preservative mixture added, it amounted to 0.1*104 CFU/g. The usage of the ready to use preservative mixture allows actively suppressing the yeast reproduction during long-term storage (seven days) of coarsely chopped fresh pork products (250 CFU/g). The optimal method for applying the preservative to fresh pork chops has been determined. Applying the preservative to coarsely chopped fresh meat by simply mixing and massaging (for example, together with spices or marinades) is the most rational method for this product type. Primary and secondary lipid degradation products are considered, and the peroxide and acid numbers of fresh meat products during 30-day storage are determined. After 30 days of storage, a noticeable increase in oxidative processes in the control sample is observed, whereby the end point of the shelf life of coarsely chopped fresh pork products has been chosen.

*We have to negligate the trade mark name of the preservative mixture by the law of advertisement (The Ed.)

2. Introduction

The problem of efficient preservation of food and raw materials at all stages of their production, storage, transportation and trade, including home food preservation, appears highly relevant today. According to some estimates, up to 25% of the world’s food produced is susceptible to the damaging effects of mold alone [1].

Current methods for preserving food products and preventing their microbiological spoilage are divided into three groups: physical, chemical, and biological ones. Physical methods include temperature (thermal and refrigeration) exposure, drying, vacuuming, etc. Chemical methods comprise salting, smoking, brining, the use of preservatives, etc. Biological ones consist in the treatment with starter and bioprotective cultures, the use of bactericides, enzyme preparations, etc [2, 3]. Each of these methods has certain limitations in the production of a particular product due to their impact on organoleptic properties and nutritional values as well as technical feasibility (for example, need for the required equipment, scarcity of the substances or preparations used). Of all the known methods for preventing microbiological spoilage, chemical preservatives are considered the most easily applicable, quickly feasible, not requiring special equipment and/or changing the manufacturing method [4, 5]. However, the meat industry is rather conservative in terms of the use of food additives, due to the fact, that chemical preservatives are allowed in the production of meat products only in limited quantities, mainly in the manufacture of jellied products and for surface treatment [6]. In addition, consumers overwhelmingly have a negative attitude to meat, labelled as containing preservatives. In this regard, the use of chemical preservatives in the production of meat products is significantly limited and cannot be regarded as universal means to prevent microbiological spoilage.

In Russia, the consumption level and production of pork has been growing rapidly recently. At that, the meat industry is dominated by pork nowadays. Pork production increased by 23% in 2020.

Pork is also a source of complete animal protein and has a high nutritional value. In addition, pork meat contains vitamins, macro- and microelements necessary for a comprehensive development of the human body [7].

For all health benefit properties to be maximally preserved, the rules of processing, transportation and storage of meat have to be observed. According to the Sanitary Rules and Norms SanPiN and Technical Regulations of the Customs Union TRCU 034/2013 “On the safety of meat and meat products”, pork belongs to the category of perishable goods.

If the storage conditions and terms are violated, the growth and reproduction of microorganisms in fresh pork significantly accelerates, which leads to an increase in bacterial contamination. Under favorable conditions, microorganisms accumulate on the surface and gradually penetrate deep into the meat, causing the product spoilage. During storage, meat loses its positive properties, its organoleptic, physical and chemical parameters deteriorate significantly, and the risk of harm to human health increases due to the vital activity of pathogenic microbial flora. There are several types of meat spoilage: putrefaction, slime production, mold formation, acid fermentation (meat souring), etc. The intensity of these processes depends on temperature, relative humidity, microorganism type, and the degree of initial meat contamination [8].

Putrid spoilage is most often found when storage conditions are violated. Putrefactive microflora causes meat spoilage. Putrefactive microorganisms can be both aerobic and anaerobic. They are able to secrete protease enzymes that break down proteins. These microorganisms include aerobic bacilli (B. pyocyaneum, B. mesentericus, B. subtilis, B. megatherium), anaerobic clostridia (Cl. putrificus, Cl. histolyticus, Cl. perfringens, Cl. sporogenes) and facultative anaerobic cocci. The end products of aerobic putrefaction are ammonia, carbon dioxide, hydrogen sulfide, and mercaptans. Each of these compounds can cause harm to a human body, which manifests as a serious intoxication [9].

Anaerobic putrefaction of pork can occur without oxygen. Therefore, even vacuum packing will not protect the meat from spoilage if storage temperature requirements are violated. The end products of anaerobic putrefaction are the products of decarboxylation of amino acids causing the formation of off-odour substances, such as indole, skatol, phenol, cresol, diamines. Their derivatives are cadaveric poisons (cadaverine, putrescine, etc.); they are toxic to humans and can cause death [10].

Slime production is a result of slime-forming microorganisms (lactic acid bacteria, yeast, and micrococci) proliferating and partially dying off on the pork meat surface. The meat storage at a temperature of 18 to 25 oC and high humidity contribute to slime production. However, some microorganisms that cause slime formation can develop even at sub-zero temperatures. During sliming, the meat surface becomes sticky, acquires a gray-green hue and a stale off-odour, the pH of the meat surface layers is 5.2 to 5.3. It is important to distinguish between slime production and the initial stage of putrefaction, as each is caused by a completely different microflora [11].

Another equally dangerous type of meat spoilage is mold formation, which occurs when microscopic fungi develop on the surface during long-term storage of the product. When mold grows, the meat quality decreases because of protein hydrolysis and deamination of amino acids. The fungi most often found on the meat surface are Mucor, Penicillium, Aspergillus and Cladosporium. They are able to grow at low temperatures (in the refrigerators). These fungi produce mycotoxins, cause food spoilage, allergic reactions and various diseases in humans [12, 13].

The goal of this paper is investigating the effect of the compounds of food additives in the preservative mixture (detailed in the section 3.1.) on the resistance of fresh pork to microbiological spoilage during storage.

3. Materials and methods

3.1. Research objects

The research objects in this paper are the follow items:

  • Coarsely chopped fresh pork (with a fat content of not more than 15% by weight)
  • The compounds of food additive preservative mixture. The content of ready to use mixture are potassium sorbate (E202), sodium acetate (E262), sodium benzoate (E211), glycerin (E422), carboxymethylcellulose (E466) and an antioxidant (dihydroquercetin). The additive is manufactured by a research and manufacturing association Russia
  • Lactic acid
  • Acetic acid
  • Sodium acetate (E262)

3.2. Research methodology

The total viable count and the amount of yeast were determined by plating the product onto agar plates with culture media, allowing microorganisms to grow and counting all individual colonies.

The peroxide value and acid value were found using the standard methods [14, 15]. Method for determining the peroxide value is based on the reaction of the oxidation products of animal fats (peroxides and hydroperoxides) with potassium iodide in a solution of acetic acid and isooctane or chloroform, followed by quantitative determination of the released iodine with a solution of sodium thiosulfate using a titrimetric method. The method for determining the acid value is based on the dissolution of a sample in a mixed solvent, and titration of free fatty acids with a solution of potassium hydroxide.

All analyses were repeated in triplicate unless otherwise stated and the average values were calculated. The results are expressed as the mean value ± standard deviation. Significant differences between the mean values at significance level p < 0.05 were identified using the one-way analysis of variance and Student’s test. Microsoft Excel version 2010 was used as the statistical analysis software.

4. Results and discussion

To identify the functional properties of preservative mixture, tests were carried out on chilled pork in comparison with control samples and the most common substances having a preservative effect (lactic acid, acetic acid and sodium acetate). A comparative assessment of microbiological indicators in meat products was carried out, wherefore the quantities of mesophilic aerobic and facultative anaerobic microorganisms (MAFAM) were monitored for 7 days at a temperature of 8 to 10 oC. The experimental results are shown in Figure 1.

Figure 1. Effect of various preservatives on the total viable count of fresh pork chops during storage

The most common indicator of meat chops spoilage is natural acid fermentation. As a rule, acid fermentation develops in muscle tissue rich in glycogen. The main signs of the process are a sour off odour, gray or greenish hue, a decrease in the tissue elasticity and, as a result, a loose consistency. The causative agents of the defect are psychrotrophic lactic acid bacteria and yeast fungi, which ferment carbohydrates to form organic acids, as well as gases (carbon dioxide and, in some cases, hydrogen). In addition to meat carbohydrates, chopped meat products also contain carbohydrates that come from onions, marinades and other ingredients. These carbohydrates located in the brine between pork cuts are a favorable medium for pathogens of acid fermentation to develop.

Our experimental studies have shown that the selected preservatives actively inhibit microbial growth during storage. Thus, on day 7, the microbial content in the control sample was 12·104 CFU/g, in the sample with lactic acid added was 2·104 CFU/g, in the sample with acetic acid added was 1.8·104 CFU/g, in the sample with sodium acetate added was 0.7·104 CFU/g, and in the sample with the compounds of preservative mixture added was 0.1·104 CFU/g.

Preventing the yeast development in meat chops is an important component of raw meat manufacturers’ success, as it directly relates to the shelf life of the product and guarantees its safety for the consumer [16]. The contamination of meat products results from contaminated workers’ hands, storage containers, unsterilized spices and onions. Figure 2 shows the effect that various preservatives produce on the yeast growth in raw meat during storage.

Figure 2. Effect of various preservatives on the yeast growth in fresh pork chops during storage

According to the research results, the classical preservatives (lactic acid, acetic acid and sodium acetate) have a weak effect on the growth and reproduction of yeast during raw pork storage. The fast growth of yeast in fresh pork chops starts on day 2 and reaches its peak value of 1600 CFU/g (control sample) on day 7. However, the use of the compounds of the preservative mixture allows actively suppressing the yeast reproduction during long-term storage of fresh pork products (250 CFU/g).

The data obtained confirm that the preservative mixture not only effectively inhibits the growth of yeast, but also exhibits a clear antimicrobial activity against a wide range of microorganisms.

On studying the microbiological indicators of coarsely chopped fresh pork, it was found that the yeast content on the brined meat cuts surface is hundreds of times higher than in the internal tissue. Given this fact, it is obviously the meat surface as well as the ingredients in the brine that should mostly be exposed to preservatives. In order to verify this statement, the microbiological indicators of raw pork prepared according to the same recipe, but using different methods for applying the preservative, were compared. In one sample, the preservative was applied with a syringe solution; in another one, it was added in a liquid form, being mixed with onions and marinade and then massaged. The control sample was prepared without any preservatives. The experimental results are shown in Figure 3.

Figure 3. Effect of the method of applying a preservative on the yeast growth in fresh pork chops

Massaging was carried out in a meat tumbler “Metat master” in accordance with the tumbling program selected. Tumbling parameters are shown in Table 1.

Table 1. Tumbling parameters

Thus, applying a preservative to raw meat chops by simply mixing and massaging (for example, together with spices or marinades) is the most rational method for this product type. In this case, two positive effects are achieved simultaneously: the preservative concentration in the area affected by yeast increases and the total amount of the preservative in the product decreases, which provides advantages from the points of view of both product safety for consumer health and economic benefit.

The study of the increase in the shelf life of the product preserved using the preservative mixture was carried out at various time periods (from 5 to 30 days), every 5 days the amounts of primary and secondary lipid degradation products being measured and peroxide and acid numbers being determined [17].

The food additive was applied with different mass concentrations (0.1%, 0.4%, 0.6% and 1%).

Based on the data obtained, the dependence of the peroxide number (PN) values of the samples on the product storage duration was determined (Figure 4).

Depending on the dosage of the preservative mixture, the PN values vary, but in all options the increasing dynamics is observed over time. The highest rate is detected in the control sample. The lowest oxidative processes are observed in the samples containing 0.6% and 1% of the preservative and having significant differences with the control sample.

Figure 4. Accumulation of primary oxidation products in fresh pork chops during storage

On day 10, all samples containing preservative mixture exhibit a sharp increase in the PN values (1.6 times on average), which causes the interaction of acetic acid contained in the marinade with the antioxidant (dihydroquercetin), accompanied by a shift in acidity towards the alkaline side. On day 15 of storage, the PN value continues to gradually increase, and the active substance of the food additive begins inhibiting lipid peroxidation throughout the storage period, demonstrating significant differences with the control sample. After 30 days of storage, a noticeable increase in oxidative processes in the control sample is observed, whereby the end point of the shelf life of fresh meat has been chosen. However, the antioxidant activity allows increasing the product storage stability.

Similar dynamics are observed in the acid number variation (Figure 5).

Figure 5. Acid number variation over the entire product shelf life

Oxygenated products with excessive acidity reduce meat quality due to moisture loss. In turn, moderate acidity of meat products reduces the product quality to a lesser degree, so it remains juicy. In addition, the antioxidant contained in preservative mixture allows increasing the shelf life.

5. Conclusions

The novelty of this research is theoretically justified, and a high performance of the compounds of food additive preservative mixture in manufacturing raw pork is experimentally confirmed. Applying the additive allows reducing losses during heat treatment and storage of the meat products, increasing yield and improving consistency, as well as reducing the cost of production and increasing the shelf life of up to 30 days. This result is ensured by the use of the latest broad-spectrum antimicrobial preparation of preservative mixture. The preparation has a significant bactericidal effect and inhibits the growth and development of yeast. The most rational way to apply the preparation into a meat system is to add it to the product by simply mixing and then massaging (for example, with spices or marinades). As the preservative contains the natural antioxidant dihydroquercetin, the preparation can be used to good advantage for products with a high fat content to prevent the lipid fraction oxidation during storage. The optimal concentrations of the preparation in the meat system is from 0.6% to 1% by weight. A higher concentration will lead to a higher price of the end product. Meanwhile, a concentration of the bio-preservative less than 0.6% by weight will reduce the product storage stability and its resistance to microbial spoilage.

6. Conflicts of interest

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the content of this paper.

7. Acknowledgement

The work was supported by Act 211 of the Government of the Russian Federation, contract № 02.A03.21.0011.

8. References

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Investigation of the shelf life of fruit yogurts as a function of the treatment of flavoring substances

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Investigation of the shelf life of fruit yogurts as a function of the treatment of flavoring substances

DOI: https://doi.org/10.52091/JFI-2021/1-3-ENG

Received: 2020. September – Accepted: 2020. December


1 Széchenyi István University, Faculty of Food and Agricultural Sciences, Department of Food Science, Mosonmagyaróvár, Hungary


yogurt making, microwave irradiation, fruit drying, microbiological parameters, total viable count, yeast count, mold count, Escherichia coli, coliform

1. Summary

Milk and dairy products represent one of the foundations of the human diet because of their valuable ingredients and pleasant sensory properties. The aim of our research was to investigate how different heat treatment processes (microwave irradiation, drying) affect the shelf life of dairy products (yogurt) from a microbiological point of view. In the course of our measurements, the effects of the different heat treatment parameters of the flavoring substances used in the production of the products (apples, bananas) on the microbiological properties of the products and, thus, on their shelf life were investigated. In our experiments, conventional drying (55 °C, 24 hours) and microwave irradiation technology (800 W, 55 °C, 10 min) were used as treatment forms of the additives. Comparisons were made in terms of microbiological parameters (total viable count, yeast/mold count and E. coli/coliform count). Based on our results, we believe that the drying process can ensure microbiological safety in food production if the air circulating in the equipment has adequate hygienic properties. The microwave irradiation technology can be used successfully to inhibit microbes in foods, in this case fruits. However, the same treatment parameters cannot be applied to different fruits.

2. Introduction and literature review

Milk has been a mainstay in the human diet since the beginning of human history. Its useful ingredients have a beneficial effect on a person’s healthy physical and mental development. The ingredients of milk are physiologically beneficial, one of the outstanding features being its high calcium content, therefore it plays a role in the bone formation of developing organisms [1], and it also contains proteins that are important and easy to use for the body. Due to all these properties, dairy products can be considered as staple foods in the human diet. In the food industry, the milk of many farm animals (sheep, goats, cattle) is processed, but in Hungary cow’s milk is consumed in the largest amount.

Yogurt is a dairy product consumed all over the world. Nutrition science professionals believe that this sour milk product has a high nutritional value (a significant part of its lactose content is broken down during fermentation and it has a significant concentration of Ca++) and beneficial bioactive effects (prebiotic ingredients and probiotic bacteria). Natural yogurt is made by adding lactic acid bacteria that induce lactic acid fermentation in the culture medium during their basic physiological activities. Of all products manufactured from milk, yogurt is the most popular worldwide [2].

In the case of fruit yogurt, when dried fruit or dried pieces are added to the yogurt, the dried products tend to absorb some of the free water in the yogurt gel, thus helping to separate the whey of the product during storage [3]. It is also an advantage of adding fruit that, according to some studies [4], the addition of 10 v/v% of fruit significantly improves the physico-chemical properties of the product. The interior of healthy plant tissues does not contain microorganisms, so the primary microbiota of plant raw materials comes mainly from the soil, water, air and, occasionally, from insects or animals. Plant parts developing in the soil (tubers, roots) and in the vicinity of the soil are usually heavily contaminated, their microflora composition is practically identical to that of the soil. Microorganisms are present on fruit surfaces in the amount of roughly 103 to 105 CFU/g, a significant part of which are lactic acid and acetic acid bacteria. However, the largest part of the microbiota is made up of yeasts, the most common of which are Hensaniaspora, Torulaspora, Pichia, Saccharomyces, Candida and Rhodotorula species. Common spoilage microorganisms in fruits include Alternaria, Aspergillus, Fusarium, Monilia and Mucor species. Fruits are excellent culture media for molds, including many mycotoxin-producing ones. Contamination of the raw material and improper storage conditions often also allow the formation of toxic metabolites. For example, patulin, a toxic substance (mycotoxin) produced by Aspergillus and Penicillum fungi, can be detected in moldy fruits (mainly apples and pears) [5].

During the technological processing of fruits, cutting, slicing, chopping and peeling increase the likelihood of cross-contamination from other materials, tools and equipment at different stages of production. In addition, the increased availability of sugars and other nutrients in minimally processed fruits contributes to the change in the microbiota and increases its population [6, 7]. The main factors in the microbiota of the raw material are the hygiene of the surface of the materials used in the production and the processing equipment, as well as the hygiene of the production environment and the food handlers, which determine the microbiological quality and safety of the final product [8, 9, 10]. The authors of a study on minimally processed plant-based foods detected high total aerobic microorganism counts on food contact surfaces, especially on peelers, knives and cutting boards [10]. The same researchers also reported high levels of facultative anaerobic bacteria of the Enterobacteriaceae family on cutting tables and cutting boards [10]. Although washing and other decontamination procedures are used in the manufacturing processes of all processing plants, it is still difficult to achieve a significant reduction in microbial contamination [11]. Favorable conditions for the growth of microorganisms present in fruits and vegetables can also develop during the packaging and storage periods. Lehto et al. discovered a large number of aerobic microorganisms in surface sampling of vegetable processing plants on devices and equipment in contact with already cleaned vegetables, as well as in the air space of storage, processing and packaging rooms [10].

In the food industry, heat treatment processes are the most important determinants of food safety. Heat treatment of milk is necessary to guarantee its microbiological safety by killing pathogenic microorganisms in milk. Several heat treatment methods are used in the food industry. The efficiency of the heat treatment is ensured by strictly defined temperatures and holding times. In addition to the raw materials of the products, it is also important to ensure the appropriate microbiological properties of the additives. „Heat treatment is an operation related to the warming or heating of milk, cream, etc., the objective of which is to reduce the number of or destroy microorganisms” [12]. Heat treatment during milk processing is a general technological step aimed at improving the shelf life of milk by inactivating microorganisms and enzymes. The use of a raw material with a favorable microbiological condition can also improve the texture quality of certain dairy products, such as yogurt [13].

Microwave technology as a heat treatment process is primarily used in households. In the food industry, it can currently only be used reliably in certain areas. The reason for this is that heat transfer is uneven in microwave equipment, and underheated or overheated places develop in the product. In the case of liquids flowing in a pipe, e.g., when treating milk with microwave energy, this can be avoided [5]. where this technique can be used, it is an advantage, as the time of treatments applied to foods can be reduced, thus making the technique economical. In addition to cost-effectiveness, an additional advantage is that the directions of heat and material transport are the same, so that a dry crust that prevents flow is not formed [14]. Areas of application include drying, thawing of frozen meat, tempering, pasteurization, sterilization and prevention of food discoloration [15, 16].

Sterilizing and antimicrobial effects are also attributed to microwave radiation. In Pozar’s experiments [17], this effect could be achieved using a frequency of 2,450 MHz, and in some cases even using a frequency of 915 MHz. Radiation increases the shelf life of foods by killing the microbes in the food and/or inhibiting their growth.

The effect of microwave radiation on microbes has been investigated in a wide variety of foods and food raw materials, especially in meats. The spreading of microwave pasteurization [18] has been facilitated by the fact that its use in foods does not cause significant damage, as opposed to traditional heat transfer methods. The reason for this is the short heat treatment and irradiation times [19, 20].

Compared to the microwave treatment technology, drying is a more traditional method, the essence of which is the extraction of most of the water content from the fruit, less often, from the vegetable, by gentle heat transfer, which leaves behind an intensely flavored concentrate of significantly lower weight and size that the starting material. Thus, microscopic organisms that remain on the dried fruit lose their viability and ability to reproduce due to a lack of available water. Fresh fruits contain 90 to 95% water, which drops below 15% after drying. In this way, spoilage caused by bacteria and molds can be prevented while retaining certain nutrients, roughage and minerals, such as iron. Compared to fresh fruits, dried fruits contain a lot of carbohydrates, fiber and antioxidants, flavonoids, phenolic acids, carotenoids and vitamins in a concentrated form [21, 22].

The food industry produces yogurt products of various compositions, but the technological processes used in their production are almost the same until the inoculation of milk. Milk is usually inoculated with a 2 to 3% starter culture and incubated at 40 to 45 °C. In this temperature range, the desired final acidity is reached in 3 to 4 hours. If a lower temperature (30-37 °C) is used, the operation takes longer (7-8 hours), but in this case excessive acidification of the product can be prevented [23].

The bacterium Streptococcus thermophilus is primarily responsible for the taste, aroma and texture of the yogurt, and is in fact able to ferment pasteurized milk on its own into yogurt, however, in addition to Streptococcus, Lactobacillus bulgaricus is also used for the fermentation to produce the acids that from in the product. S. thermophilus and L. bulgaricus are usually used simultaneously, in a 1:1 ratio, when inoculating the milk (pH 6.6). Their proportion changes as the fermentation progresses [24].

3. Materials and methods

Manufacture of the products

For the manufacture of the products, raw, untreated milk and 2.8% fat UHT drinking milk (Mizo) were used, which were mixed in a 2:1 ratio before making the yogurts. Raw milk was pasteurized on a hot plate at 75 °C for 15 minutes to achieve adequate initial microbiological safety, and then the drinking milk was added. After heat treatment, the temperature of the milk was allowed to drop to 30 °C, it was inoculated with the amount of thermophilic yogurt culture (Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus thermophilus, YF-L812, Chr. Hansen, France) according to the instructions for use, and then it was stirred for 15 minutes to ensure proper homogeneity. The inoculated milk was dispensed into 2 dl plastic yogurt cups and the cups were placed in a 43 °C thermostat (Binder, Germany), where they were allowed to curdle for 7 hours (pH 4.6). After acid curdling, the fruits treated with the following procedures were mixed into the yogurts.

In our experiment, with the exception of the control sample, two types of heat treatment procedures were used for the fruits, microwave irradiation and a conventional heat treatment method (drying).

The samples prepared in the course of the experiment:

  • Sample 1: fruit yogurt with the addition of raw apples (Ny-A)
  • Sample 2: fruit yogurt with the addition of raw bananas (Ny-B)
  • Sample 3: fruit yogurt with the addition of dried apples (A-A)
  • Sample 4: fruit yogurt with the addition of dried bananas (A-B)
  • Sample 5: fruit yogurt with the addition of microwave-treated apples (MH-A)
  • Sample 6: fruit yogurt with the addition of microwave-treated bananas (MH-B)

Raw fruits were processed in a clean, impeccable condition free of bruises and defective parts, at the optimum degree of ripeness.

For the microwave treatment, a MARS 5 (CEM Corporation, USA) microwave digestion oven was used. Diced raw apples and bananas were placed in the sample holder of the microwave apparatus and subjected to microwave irradiation. The energy transfer program on the device was set to heat the fruits to 55 °C when a power of 800 W with 100% efficiency and with a holding time of 10 minutes was applied, in a total of 15 minutes. Temperature detection and control was performed using a sensor (RTP 300) introduced into the sample holder.

The fruits used in the drying process were cut into pieces of equal size (0.5 cm), so that the drying time would be the same, and then they were placed in a drying apparatus for 24 hours at 55 °C. The dried and microwave-treated fruits were then ground. The knives and the grinder were treated with Mikrozid disinfectant before use. 5 grams each of the ground fruits were added to 150 ml of the already prepared yogurt samples. Until further analysis, the yogurt-dried fruit mixtures were stored in a refrigerator at 4 °C.

3.2. Product shelf-life analysis

The product were tested for 4 weeks in terms of shelf life. Analyses were carried out on days 0, 7, 14, 21 and 28. Microbiological properties (total viable count, yeast/mold count, E. coli/coliform count) were tested every week from the time of production. The experiment was carried out with 3 parallel measurements (n=3) on each sampling day, i.e., with 15 samples for each original sample (Ny-A; Ny-B, A-A; A-B; MH-A; MH-B), meaning that a total of 90 samples were processed.

A plate pouring method was used to grow the microorganisms. From food safety and technological hygiene point of view, a total viable count of 105/cm3 is the critical limit for raw milk, because normal pasteurization procedures can still be used with sufficient efficiency at this microbe count.

The determination of the total viable count was carried out on a PC (Plate Count, Biolab) medium, with an incubation time of 72 hours at 30±1 °C [25]. By culturing on a selective medium prescribed in standard MSZ ISO 7954:1999 at 25 °C, yeasts and molds form colonies. YGC agar (Yeast Extract Glucose Chloramphenicol Agar, Biolab) was used for their detection, as prescribed by the standard. This selective medium is suitable for isolating and counting yeasts and filamentous fungi from milk and dairy products. Plates were incubated at 25±1 °C for 48 hours, after which the colonies developed on the plates were counted [26].

Co-determination of the coliform count and the E. coli count can be accomplished using CC agar (ChromoCULT Coliform Agar, Biolab). Differentiation between the colonies is aided by the fact that coliform colonies are salmon red, while the color of E. coli colonies ranges from dark blue to violet. Incubation parameters for E. coli/coliform were 24 hours and 35-37 °C [27].

Our measurement results were plotted using Microsoft Office Excel 2016®. During the evaluation of the microbiological results, microbe counts were displayed in a logarithmic form: the slope values of the lines fitted to each point characterize the exponential growth phase of the microorganisms.

4. Results and evaluation

4.1. Test results of the yogurt samples with apples

4.1.1. Total viable count

According to Figure 1, on days 0, 7 and 14 of the measurement, the total viable count showed almost the same results for the yogurt with dried apples and the yogurt with microwave-treated apples. The yogurt with raw apples already showed higher total viable count values in the second measurement (day 7) compared to the other two samples. Here we already saw a significant difference between the cell counts, which difference only increased over time (day 14). In the case of yogurts with microwave-treated apples and dried apples, the rates of increase in cell counts were approximately the same. This result is also supported by the slope values marked in Figure 1a.

Figure 1. Results of the determination of total viable count in the case of yogurts with apples

4.1.2. Yeast/mold count

Based on Figure 2, it can be concluded that from the first measurement data to the last measurement result, the yogurts with microwave-treated apples and with dried apples showed significantly lower yeast counts than the yogurt with raw apples. There was no difference of the same order of magnitude between samples MH-A and A-A, however, on day 21 of the measurement, there was a clear, significant difference in favor of sample MH-A. Based on this, microwave heat treatment proved to be more effective in inhibiting the activity of yeasts, using the treatment settings applied by us.

In the case of yogurts with apples, it is clear that the microwave technology proved to be the best treatment for both the total viable count and the yeast/mold count. The yogurt with dried fruit exhibited similar cell counts and growth tendencies. However, at the end of the storage time, larger differences between the cell counts developed here. In terms of shelf life, the worst results were obtained for the samples with raw fruit. Differences of an order of magnitude were measured compared to the other two samples, there were significant differences (p≤0.05).

Figure 2. Results of the determination of yeast count in the case of yogurts with apples

On day 21, at the third sampling time, with the exception of yogurts with microwave-treated apples, yogurts with raw and dried apples were spoiled. After the third measurement, in addition to the high yeast count, a significant mold count was also detected in the yogurts with raw or dried apples. In contrast, in yogurts with microwave-treated apples, no mold colonies could be detected after the third measurement.

For the mold count, under the current regulation [27], the level of compliance (m) is 102 CFU/cm3 for fermented milk, dairy products, sour dairy products, cottage cheese and cottage cheese products, while the rejection limit value (M) is 5*103 CFU/cm3.

In terms of mold count, the presence of no molds was detected in yogurts with apples during the first two measurements, on days 0 and 7. On day 14 of the experiment, colonies of mold appeared in the samples with raw and dried apples, already with a value above the rejection limit as defined by the regulation in the case of raw apples (3*104 CFU/cm3). However, in the case of the product with dried apples, the number of mold colonies remained at an acceptable level (2.2*102 CFU/cm3) according to the relevant regulations [27].

4.2. Test results of the yogurt samples with bananas

4.2.1. Total viable count

In the case of yogurts with bananas, it was found that the two types of treatment procedures (drying, microwave) also have an effect on the microbial count. In the case of the microwave-treated sample, the increase in the total viable count was not significant until day 21 of the experiment compared to the initial TVC (Figure 3). On the other hand, the total viable count increased from week to week for the yogurts supplemented with raw or dried fruits. In addition, it was also found that the total viable count of the sample supplemented with dried fruit had the highest total viable count, and the most intense increase in the TVC was also observed in this sample. Already on day 7 of the storage experiment, there were significant differences between the test results of the samples, with an order of magnitude difference between sample A-B and samples Ny-B and MH-B. On day 14 of the experiment, orders of magnitude differences were observed between the date of all three samples. In terms of total viable count, the increase in TVC was the lowest in the case of sample MH-B.

Figure 3. Results of the determination of total viable count in the case of yogurts with bananas

4.2.2. Yeast/mold count

Based on the yeast count results (Figure 4), it was found that there was no significant difference between the yogurts with raw and microwave-treated bananas in terms of the colony counts of the samples and the growth trends of the microorganisms. However, yogurts with dried apple were characterized by a rapid increase in cell number, which also affected the organoleptic properties of the product. From day 7 of the experiment, there were already significant differences between samples MH-B and Ny-B and samples A-B and Ny-B. Microwave treatment proved to be the most effective in this case as well.

The evolution of the mold count during the shelf life was examined also in the case of yogurts with bananas. The results showed that during the first two measurements, on days 0 and 7, no mold colonies developed. However, on day 14 of the experiment, molds appeared in an amount of 1.4*104 CFU/cm3 in the sample with dried bananas, a number which well exceeds the compliance limit value according to the regulation (102 CFU/cm3), moreover, it falls into the rejection category (5*103 CFU/cm3). For the other two samples (raw and microwave-treated bananas), no molds were present on day 14. On day 21 of the experiment, molds also appeared in the yogurt supplemented with raw bananas in an amount of 3.0*101 CFU/cm3, which does not yet exceed the compliance limit value. Mold was still not detectable in sample MH-B. On day 28 of the experiment, the mold count of the yogurt with raw bananas also exceeded the rejection limit value by approximately 1 order of magnitude. No mold could be detected in sample MH-B even on day 28.

The results obtained for dried products suggests that the 24-hour drying with a gentle heat treatment did not sufficiently improve the microbiological condition of the materials used. It can be assumed that the hygienic condition of the air flowing through the drying apparatus was also inadequate. We believe that fruits prepared for yogurt products should only be dried in a room and equipment that has impeccable air, and have exhaust and adequate air filtration systems.

4.2.3. E. coli/coliform results of the yogurts

The bacterium Escherichia coli is the most important microbe in the normal intestinal flora, making it a natural component of the digestive system of all warm-blooded animals and humans. It can enter foods from fruits and vegetables if they had not been cleaned thoroughly enough, but it can also be found in raw milk or dairy products made from it.

Figure 4. Results of the determination of yeast count in the case of yogurts with bananas

Under current regulation [28], the compliance level is (m)<1/CFU/cm3 for fermented milk, dairy products, sour dairy products, cottage cheese and cottage cheese products, while the rejection limit value is (M)<10/CFU/cm3.

During the tests carried out on days 0 and 7 of the experiment, no E. coli bacteria were detected in any of the samples prepared by us. However, on day 21 (week 3) of the experiment, the bacterium became detectable in all yogurts except the samples with raw bananas and microwave-treated bananas. By week 4 of the experiment, E. coli also appeared in the yogurt with raw bananas. Thus, by the end of the study, only the yogurt supplemented with microwave-treated bananas met the legal requirements.

Coliform bacteria are found in wetlands, in soil and on the vegetation, and are usually present in large numbers in the feces of warm-blooded animals.

According to the relevant regulation (EüM decree 4/1998 (XI. 11.) – EÜM: former Ministry of Health Affairs), the compliance level is (m)<10 CFU/cm3 for fermented milk, dairy products, sour dairy products, cottage cheese and cottage cheese products, while the rejection limit value is (M)<102 CFU/cm3.

Coliform bacteria were detected in all samples on day 0 of the experiment, however, the compliance limit value was exceeded only by the results of the yogurt samples supplemented with dried fruits. After 1 week, however, coliforms could only be detected in the yogurt with dried bananas. It is likely that the decrease in the pH value of the yogurt prevented the bacteria from growing and surviving.

At week 3 of the experiment, coliform bacteria were detected in the samples supplemented with raw fruits, they were not present in the other samples. In our case, the samples supplemented with raw fruits reached the M value, so after 21 days the products were not suitable for human consumption.

During the microbiological studies, the determination of Salmonella and Staphylococcus aureus was also performed, as required by the regulation. These tests were negative in all cases.

Schnabel et al. infected raw fruits with seven microbial strains (including the E. coli bacterium also tested by us) with a cell count in the 108 order of magnitude. The samples were then treated with microwave-assisted plasma, which reduced the cell count by 4 orders of magnitude already after 5 minutes of treatment. The treatment was performed under non-thermal conditions (at 30 °C), thus excluding the microbicidal effect of the temperature [29].

Picouet et al. showed that microwave treatments had a similar effect on the E. coli O157: H7 and total viable count values, i.e., a 1.01-1.16 log CFU g-1 decrease was detected. The same treatment parameters greatly affected L. innocua, with population below the detection limit (10 CFU g-1) in most cases. In apple puree samples, the total viable count remained stable during storage at 5 °C, with a slight increase on day 14 [30]. This trend was also observed during our own measurements. Our results confirm that the objective of our research was achieved, which was to verify the microbicidal and inhibitory effect of microwave treatment.

Our results are also supported by the fact that 5 to 25 seconds of microwave treatment (65 °C, 1200 W, 2.45 GHz) can reduce the Salmonella cell count in vegetables by 4 to 5 orders of magnitude, thus confirming the stronger microbicidal effect of microwave treatment compared to other ones [31].

5. Conclusions and recommendations

When using fruits as flavoring agents in yogurts, two types of heat treatment were applied to increase the shelf life of the products. The effect of the microwave treatment method on shelf life was characterized by the length of shelf life after the addition of conventional and untreated fruits to yogurt.

Based on the microbiological studies, it was found that microwave treatment was the most effective of the various heat treatments. Of the methods of heat treatment of fruits, microwave irradiation resulted in a lower total viable count compared to untreated fruits and drying technology.

Based on our microbiological results, we believe that the contamination or texture of the raw fruit fundamentally influences the effectiveness of the treatment. After microwave treatment of bananas, the presence of E. coli could not be detected in the yogurt by the end of our experiments (day 28), as opposed to the treated apples, where its presence was already detected on day 14. This may be noteworthy because the presence of E. coli was not detected in either case on the day the products were prepared. It can be assumed that microwave irradiation exerted a more intense germicidal effect in the softer texture of bananas than in apples which have a harder consistency.

It was found that the drying procedure is suitable for the production of microbiologically safe food if the microbiological condition of the air circulating in the equipment is also adequate.

Based o our results, it is hypothesized that microwave irradiation technology can be applied successfully to foods, in this case fruits, to inhibit microorganisms living inside and on the surface of fruits.

While in the case of yogurts flavored with apples, the microbiological characteristics of samples with raw fruit were worse, in the case of bananas, the drying technology proved to be the most unfavorable from a microbiological point of view. The most likely reason for this may be that, compared to apples, bananas contain on average three times more carbohydrates which became more concentrated as the result of drying. This high carbohydrate fruit mixed with the yogurt may have served as a culture medium for various microorganisms.

In order to determine whether or not the use of different microwave temperatures (other than 55 °C), power and treatment times would lead to better shelf-life results, further tests are required.

Of the heat treatment procedures, microwave may be suitable both for treating milk, thus reducing the number of microbes, and for reducing the total viable count of the flavoring agents (spices, fruits, vegetables) used.

6. Acknowledgment

This publication was supported by project no. EFOP-3.6.1-16-2016-00024 titled „Developments for intelligent specialization in cooperation between the University of Veterinary Medicine and the Faculty of Agricultural and Food Sciences of Széchenyi István University. The project was supported by the European Union and co-financed by the European Social Fund.

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Investigation of the antibiotic resistance of staphylococcus species isolated from foods

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Investigation of the antibiotic resistance of staphylococcus species isolated from foods

DOI: https://doi.org/10.52091/EVIK-2021/2-1-ENG

Received: February 2021 – Accepted: April 2021


a University of Debrecen, Faculty of Agricultural and Food Sciences and Environmental Management
b BIOMI Kft.
c Pázmány Péter Catholic University
d WESSLING Hungary Kft.
e University of Veterinary Medicine
* Corresponding author: horvath.brigitta920108@gmail.com


food, Staphylococcus, antibiotic resistance, MALDI-TOF- MS, bacterial identification, food safety, human pathogen, nosocomial infection

1. Summary

The presence of methicillin-resistant Staphylococcus aureus (MRSA) strains in the food chain has been confirmed by several studies in the European Union, but there are only limited data available in Hungary. The objective of the present study was to investigate the antibiotic resistance of Staphylococcus strains isolated from foods, using classical microbiological, molecular biological methods and the MALDI-TOF-MS technique, as well as the multi-locus sequence typing (MLST) of antibiotic resistant strains. During the study, 47 coagulase-positive (CPS) and 30 coagulase-negative (CNS) Staphylococcus isolates were collected. In the course of the MALDI-TOF-MS investigations, all CPS isolates (n=47) were found to be S. aureus species, while 8 different species were identified in the case of the CNS strains. Methicillin resistance was confirmed in two S. aureus strains, one of which had a sequence type not yet known, while the other MRSA strain was type ST398, which is the most common type of MRSA strain isolated from farm animals in the EU/EEA.

(The abbreviation “MRSA” is often used in common parlance, but occasionally in the literature to denote “multidrug-resistant Staphylococcus aureus”. In the authors’ manuscript - the methicillin-resistant pathogen is correctly designated as such. Ed.)

2. Introduction and literature review

The number of nosocomial infections caused by antibiotic-resistant microorganisms has been increasing in all countries, thus posing a greater and greater challenge to the health care system [1, 2]. The situation is further exacerbated by the fact that antibiotic-resistant Staphylococcus species have already appeared not only in communities and health care, but also in intensive animal husbandry and thus in the food chain [3].

In Staphylococcus species, genes associated with antibiotic resistance and virulence are found in the mobile genetic elements (MGE), such as chromosome cassettes, pathogenicity islands, plasmids or transposons [4]. The mecA gene is responsible for methicillin resistance: the gene encodes a modified penicillin-binding protein that reduces the binding affinity of most beta-lactam antibiotics, such as penicillin and methicillin. The mecA gene is located on the Staphylococcus chromosome cassette (SSCmec), which is a group of MGE found only in Staphylococcus species [5]. The transfer mechanism of the mecA gene between Staphylococcus species is unknown, however, evidence supports horizontal gene transfer between coagulase-positive and coagulase-negative Staphylococcus species [6].

The presence of methicillin-resistant Staphylococcus aureus (MRSA) strains in the food chain has already been reported in several studies. Some of their authors examined strains isolated from food samples of animal origin, others investigated strains isolated from raw meat samples (pig, fish, poultry). In the Netherlands in 2009, 2,217 different food samples were analyzed, 12% of which contained MRSA strains [7], while in a Danish study 4.6% of 153 pork samples and 7.5% of imported pork samples were infected with MRSA strains [8]. MRSA strains have also been identified in Germany in raw milk, pork, turkey and broiler chicken [9]. In Hungary, 27 MRSA isolates were identified in the 595 individual milk samples of a dairy farm [10], while in another study only 4 strains out of the 626 S. aureus isolates of 42 farms proved to be methicillin-resistant [11]. However, beyond these examples, the presence of MRSA in foods from other categories and ready-to-eat foods has not been investigated so far. Molecular typing results of the strains have shown that many types of MRSA are present in the food chain in different countries [12], but the most common type is CC398, accounting for 85% of the MRSA strains isolated from farm animals in the EU and the EEA [13, 14, 7,15].

The presence of additional methicillin-resistant Staphylococcus (MRS) species in foods has been investigated by fewer studies. In Nigeria, 13 Staphylococcus species (S. xylosus, S. epidermidis, S. simulans) showed methicillin resistance out of 255 isolates from traditional foods [16]. In a study in Poland, out of 58 strains isolated from ready-to-eat foods, 33 Staphylococcus strains (S. epidermidis, S. simulans, S. xylosus, S. hycus, S. lentus, S. saprophyticus) showed resistance to at least one type of antibiotic [17].

In the European Union, testing for antibiotic resistance in Staphylococcus strains isolated from foods and farm animals is currently voluntary, so in 2016 only Germany, Switzerland, Denmark and Spain reported information related to this topic. The incidence of MRSA varied from country to country, but in the case of a comparison it should be taken into account that the studies were performed on strains isolated from different animal species, meats and meat products [18]. A small proportion of human infections can be traced back to MRSA strains of the CC398 type, and they are also mainly limited to occupational exposures, such as veterinary medicine and intensive animal husbandry. Nevertheless, the virulence factors detectable in CC398-type MRSA strains allow for high pathogenicity, so continuous revision is essential both in animals and in foods [19]. The need for surveillance is also justified by the possible presence of antibiotic resistance of other Staphylococcus species, which allows for the spread of resistance and poses a risk to consumer health.

A prerequisite for a successful surveillance system is the availability of a uniform, economically acceptable, rapid and reliable method for the species-level identification of the microorganisms and the determination of antibiotic resistance, a promising cornerstone of which could be matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) based on peptide identification. In the early 2000s, several studies reported specific fragment ions that allow rapid identification of antibiotic-resistant Staphylococcus strains. The most often studied biomarker was the fragment ion with an m/z value of 2,414, the appearance of which in the mass spectrum correlates with the expression of psm-mec, characteristic of MRSA strains [20]. The applicability of the 2,414 m/z fragment ion for detection and discrimination has been demonstrated in several studies [21, 22].

In addition to the studies of the biomarkers of MRSA strains, methicillin resistance-specific fragment ion peaks of other Staphylococcus species have been analyzed in other studies. In an earlier article, two specific fragment ion values were determined: the ion fragment peak with an m/z value of 7,239, which is a biomarker of methicillin-resistant S. epidermidis, and the fragment ion peak with an m/z value of 9,674, which is the biomarker of methicillin-resistant S. haemolyticus [23].

The objective of our own experiments was to investigate the methicillin resistance of Staphylococcus strains isolated from foods using classical microbiological, molecular biological methods and the MALDI-TOF-MS technique, as well as the multi-locus sequence typing (MLST) of antibiotic-resistant strains for the epidemiological study of the strains.

3. Materials and methods

3.1. The isolates collected and culture conditions

77 Staphylococcus isolates, isolated according to the requirements of standard MSZ EN ISO 6888-1:2008, were analyzed in the Microbiological Laboratory of WESSLING Hungary Kft. in the period between August 2019 and September 2020. The isolates were grown on a Baird-Parker (Biokar, France) selective culture medium at 37 °C for 24±1 hour and colonies characteristic of Staphylococci were inoculated onto Columbia blood agar (Neogen, UK) (37 °C, 24±1 hours). In the course of culturing, 47 strains showed a positive coagulase reaction, while 30 isolates proved to be coagulase-negative, which was also confirmed by a latex agglutination rapid test (PASTOREX™ STAPH-PLUS). Isolates were collected from raw meat, meat products and ready-to-eat foods: poultry (n=14), beef (n=5), pork (n=42), game (n=1), fish (n=1), dairy product (n=3), ready-to-eat foods (n=3), vegetables (n=2) and dry pasta (n=6).

3.2. Identification of the isolates using the MALDI-TOF-MS technique

The 77 isolates collected were identified using a Bruker Microflex LT MALDI-TOF mass spectrometer and the MALDI BioTyper 3.1 (Bruker Daltonics) software. A formic acid suspension protocol was used in which a single colony was collected from the Columbia blood agar using a sterile loop, and then it was suspended in 40 µl formic acid. To the suspension was added 40 µl of acetonitrile, 1 μl of which was applied to one of the positions of the plate. After the solvent evaporated, 1 μl of α-HCCA (10 mg/ml α-Cyano-4-hydroxycinnamic acid) matrix solution was applied and the solvent was allowed to evaporate once more. 6 parallel measurements were performed for each sample.

To identify the isolates, the MALDI Biotyper 3.1 software was used, which compares the mass spectra obtained with the reference mass spectra in its database and calculates a compliance factor (score). In case of a log score value of 2.300 – 3.000, identity is highly probable. At a log score value this high, the species is considered to be identified. If the log score value is between 2.000 and 2.299, the identity is less certain, so in this case only the genus of the microorganism can be considered identified. When the log score value is between 1.700 and 1.999, even the identification of the genus cannot be considered sufficiently certain. If a log score value between 0.000 and 1.699 is returned by the evaluation software, identification should be considered unsuccessful. Identification of the coagulase-positive Staphylococcus strains included in the study was carried out earlier [24].

3.3. Antibiotic susceptibility testing

3.3.1. Investigation of the methicillin resistance specific peaks by the MALDI-TOF-MS method

The mass spectra obtained were exported to the flexAnalysis 3.4 software (Bruker Daltonics) and manual analysis and comparison of the mass spectra was performed. Smoothing of the mass spectra was carried out with the Savitzky–Golay filter, while baseline correction was performed using the TopHat algorithm. During the analysis the presence of methicillin resistant-specific fragment ion values was examined (Table 1).

Table 1. Methicillin resistance (MR) specific peaks analyzed in this study

3.3.2. Disk diffusion method

When examining the antibiotic resistance of the strains, the guidelines of the CLSI (Clinical and Laboratory Standards Institute, 2019) were followed [25]. A bacterial suspension equivalent to 0.5 McFarland unit was applied to the surface of a Mueller-Hinton agar (Oxoid, UK), and then Cefoxitin 30 μg disks were placed on the surface of the medium. The strains were incubated at 37 °C for 18 hours. In the case of MRSA strains, the reference range of the clearance zone was 6-19 mm volt, while for mecA negative species it was 20-32 mm.

3.3.3. Selective differentiation agar

In addition to the above, CHROMagar MRSAII selective differentiation medium (BD, UK) was used for the detection of methicillin-resistant Staphylococcus aureus species in the antibiotic resistance assays. Isolates were incubated at 37 °C for 24 – 48 hours under aerobic conditions. Strains that formed mauve colonies, morphologically similar to those of Staphylococci, were considered MSRA bacteria. The disk diffusion method (Cefoxitin 30 µg) and the MRSA CHROMagar assay were repeated twice for each strain isolated from a food (n=77). During the study, the reference MRSA strain ATCC 33591 was used as a positive control and the MRSA strain ATCC 29213 was used as a negative control.

3.3.4. mecA gene complex

Detection of the mecA gene was performed according to the protocol of the Danish National Food Institute (NFI), published in 2012 [26]. During the study, MRSA strain ATCC 43300 was used as a positive control and MRSA strain ATCC 29213 was used as a negative control. Genomic DNA was isolated from the bacteria and the mecA gene sequence was amplified using PCR. The primers used are listed in Table 2.

Table 2. Primers used for the amplification of the mecA gene

3.4. MLST study of methicillin-resistant Staphylococcus strains

According to the study of Thomas et al. [27], genomic DNA was isolated from the bacteria, and then the gene sequences specific for the 7 Staphylococcus aureus species were amplified using PCR (Table 3). The nucleotide sequences of the purified PCR products were determined and the sequence data were evaluated in the BioNumerics 7.6 software.

Table 3. Genes used in the MLST method and data of the primers used in their amplification

4. Results

4.1. Identification results of the isolated strains

In the MALDI-TOF-MS study, all coagulase-positive Staphylococcus (CPS) strains (n=47) were found to be S. aureus species (Tables 4 and 6). In the case of coagulase-negative Staphylococcus (CNS) strains, 8 different species (S. xylosus, S. saprophyticus, S. pasteuri, S. epidermidis, S. warneri, S. chromogenes, S. piscifermentans, S. haemolyticus) were identified (Tables 4 and 7). 30% of the CNS isolates (n=30) were found to be S. warneri species, while 23% were found to be S. pasteuri species. 70% of the S. aureus strains and all of the CNS strains were isolated from meat and meat products (Figures 1 and 2). In the case of S. aureus strains, 64% of the meats and meat products came from pigs, while this was true for 70% of the CNS strains. Within meat and meat products, the distribution of isolates coming from poultry and beef was nearly the same.

Figure 1. Food types tested
Figure 2. Raw materials of meats and meat products

The mean identification log score values of the isolates and their standard deviations are summarized in Table 4. The mean identification log score value of S. aureus isolates exceeded 2.400. The lowest log score value was 2.304, and even in this case, identification can be considered safe. When examining CNS isolates, each species was identified with a log score value above 2.300 and the standard deviation did not exceed 0.1 in any of the cases.

Table 4. Identification log score values of the identified coagulase-positive and -negative Staphylococcus species

4.2. Methicillin resistance results determined by the MALDI-TOF-MS technique

In the analysis of the mass spectra obtained from the isolates, 3 antibiotic resistance-specific peaks were examined. The m/z 2,414 peak is a protein product of the mecA gene [28], so the presence or absence of this peak was examined for all strains. The detectability of the m/z 7,239 peak was examined only in S. epidermidis species, while the presence/absence of the m/z 9,674 peak was examined only in S. haemolyticus species due to the species specificity of the peaks.

The m/z 2,414 peak was detected in two S. aureus strains out of 77 isolates, one of which came from goose liver (SA-17), while the other came from pork butt (SA-47). For the additional 75 isolates, this peak did not appear even at a low intensity (Table 5). In the analysis, mass spectra of the two S. aureus strains that proved to be methicillin-resistant were marked in red, while the mass spectra of the other S. aureus strains that did not have a methicillin resistance-specific peak were marked in black (Figures 3 and 4).

Figure 3. Mass spectrum of the m/z 2,414 transition
Figure 4. Mass spectra of the 47 Staphylococcus strains
Table 5. Frequency of specific ion fragment values in Staphylococcus strains isolated from foods

The m/z 7,239 peak could not be detected in any of the S. epidermidis strains (n=4), while the m/z 9,674 peak did not appear in any of the 4 S. haemolyticus species.

4.3. Results of the disk diffusion method and the MRSA CHROMagar selective differentiation agar

In the study of the 77 strains, the diameter of the clearance zone ranged from 23 to 29 mm in the case of 75 strains. The strain isolated from goose liver (SA-17) had a clearance zone with a diameter of 9 mm, while the strain isolated from pork butt (SA-47) had a clearance zone with a diameter of 17 mm, and the same strains also formed mauve-colored colonies on the MRSA CHROMagar selective differentiation medium (Tables 6 and 7).

Table 6 Antibiotic resistance test results of the S. aureus strains identified in foods
Table 7. Antibiotic resistance test results of the coagulase-negative Staphylococcus strains identified in foods

4.4. mecA gene detection results

Based on the results of the MALDI-TOF-MS analyses, the disk diffusion method and the MRSA selective differentiation medium, it was found that the S. aureus strains isolated from goose liver and pork butt (SA-17, SA-47) carry methicillin resistance, and this was confirmed by the mecA gene responsible for PBP2a synthesis, which could also be detected in the two strains (Table 6).

4.5. MLST types of the MRSA strains

MLST typing of the two MRSA strains was also performed during the study, using data available on the PubMLST website (https://pubmlst.org/saureus/). Of the two MRSA strains, the BioNumerics 7.6 software could only assign the sequence type in the case of the strain isolated from pork butt. The strain isolated from goose liver belonged to a sequence type not yet known, while the strain isolated from pork butt belonged to sequence type 398 (Table 8).

Table 8. MLST types of the MRSA strains isolated from foods

5. Summary and conclusions

During the study, 77 Staphylococcus isolates were collected from various food matrices according to the methods described in standard MSZ EN ISO 6888-1:2008. Although the standard allows the separation of coagulase-positive and coagulase-negative Staphylococcus species, it does not allow species identification, which is significant because of the different virulence factors and pathogenicities of the species. Identification of the 47 coagulase positive and 30 coagulase-negative Staphylococcus strains isolated from foods was performed using the MALDI-TOF-MS technique, with high identification log score values. In addition, by analyzing the mass spectra obtained and based on methicillin resistant-specific ion fragment values determined in previous studies, methicillin resistance was found in two S. aureus strains, which was confirmed by the disk diffusion method, selective differentiation agar and the detection of the mecA gene. Thanks to the specific ion fragment values, the diagnostic time can be significantly reduced, which is not negligible from economic and therapeutic points of view. However, it should be taken into consideration that due to the high variability of MRSA strains, the sensitivity and specificity of these ion fragment values are not 100%, so confirmatory studies are required.

Multi-locus sequence typing (MLST) of the two MRSA strains isolated from foods was also carried out for the epidemiological study of the strains. The isolate coming from pork belonged to type ST398, which is the most common type of MRSA strain isolated from farm animals in the EU/EEA. However, taking into account the specific host adaptation capabilities of type ST398 strains, which allow them to adhere not only to pigs, but also to other animal species and the human body, contamination and infection may occur in a number of ways during the technological steps in food processing.

Given that 2 of the 47 S. aureus strains isolated from foods proved to be methicillin-resistant, this fact confirms the dangers posed by globally increasing antibiotic resistance, thus indicating the severity and urgency of the situation.

6. Acknowledgment

This study was carried out with the professional support of WESSLING Hungary Kft., BIOMI Kft. and the New National Excellence Program of the Ministry for Innovation and Technology, code no. ÚNKP-19-3-III.

7. Irodalom

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The effect of lactation number and lactation stage on milk yield, on the composition and on the microbiological properties of raw cow milk in a Hungarian dairy farm

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The effect of lactation number and lactation stage on milk yield, on the composition and on the microbiological properties of raw cow milk in a Hungarian dairy farm

DOI: https://doi.org/10.52091/EVIK-2021/2-3-ENG

Submitted: July 2020 – Accepted: November 2020


1 University of Debrecen, Faculty of Agricultural and Food Sciences and Environmental Management, Institute of Food Science
2 University of Debrecen, Faculty of Agricultural and Food Sciences and Environmental Management, Institute of Animal Science, Biotechnology and Environmental Protection, not independent Faculty of Animal Husbandry
3 University of Debrecen, Doctoral School of Animal Science


lactation number, lactation stage, cow’s milk, milk quantity, milk composition, microbiology

1. Summary

Changes in the composition and hygienic properties of milk affect producer price, so it is essential for the responsible dairy farmer to collect information on changes in these parameters due to various factors. In their study, the authors seek to answer the question whether there is a fluctuation in the daily milk yield of cows and in the composition (fat and protein content) and microbiological properties (somatic cell count, total plate count, coliform and S. aureus count) of raw cow’s milk in primiparous and multiparous cows or at different stages of their lactation. Based on the data of a Hungarian large-scale dairy farm, it was found that there was no difference in the fat and protein content of the milk, but the daily milk yield was higher in the case of multiparous cows and, compared to the milk of primiparous cows, their milk had a higher somatic cell count and larger amounts of coliform bacteria. The daily milk yield decreased in the successive stages of lactation, but the fat and protein content of the milk increased, which is presumably due to the concentrating effect of the decreasing milk yield. No significant change was observed in the colony count of microorganisms at the different stages of lactation.

2. Introduction

Cow’s milk has a high nutritional value; it contains fats, proteins, carbohydrates, vitamins and minerals, among other things [1]. Examination of the composition of milk is a routine practice on dairy farms for monitoring the hygiene, nutritional and health aspects of dairy cows [2]. The composition of milk can be influenced by a number of factors, such as the number of lactations, the stage of lactation, the season and the feeding technology [3, 4, 5]. Thus, the composition of milk may vary during lactation, and as a result of the interactions of different environmental factors, there may be differences between the different dairy farms [6]. According to Dürr et al., the creation of databases in order to determine the causes and consequences of differences in milk yield and milk composition is of paramount importance. A database should also include records related to these parameters, as well as to lactation-related events and to the individual cows [7].

Due to its nutritional value, high water activity and neutral pH, milk serves as an excellent medium for various microorganisms, which may include pathogenic organisms such as Campylobacter jejuni, Salmonella spp., Staphylococcus aureus, Listeria monocytogenes, Yersinia enterocolitica, etc. [8, 9]. During the primary infection of milk, sick animals themselves are the sources of infection. In case of dairy animals suffering from a systemic disease accompanied by the spread of pathogens, the pathogens may be excreted in the milk. During secondary contamination, the contamination of milk is of environmental origin. Due to improper milking hygiene, milk can be contaminated by the faeces of the animals or the equipment used in milking (milking machines, milk lines, milk storage tanks), among other things [10]. As the milk enters the teat cistern and then the teat canal, it can become infected with various microorganisms, of environmental origin, so the bacterial infection of the first milk jets is remarkably high. At the beginning of milking, it is therefore advisable to separate the first jets of milk from milk that is milked subsequently, and to ensure that they are destroyed [11]. To reduce the number of bacteria in milk, heat treatment is most commonly used. The initial microbiological state of the milk is not only important from a food safety point of view, but can also affect the quality of the dairy products made from it [12].

Coliform bacteria can cause mastitis in dairy animals. Mastitis caused by coliform bacteria can reduce milk production in dairy animals, causing economic losses to dairy farms [13]. The presence of these bacteria in the environment is common, so their presence in food may indicate environmental contamination [14, 15].

Raw milk can be contaminated with S. aureus from a number of sources, such as the environment, milkers’ hands, milking equipment, and so on [16]. The economic damage due to mastitis caused by S. aureus comes from a decrease in the quantity and quality of the milk produced, an increase in the number of somatic cells measured in it, a reduction in the purchase price of lower quality milk, which also leads to a decrease in the turnover of dairy farmers [17]. Prevention is an effective means of controlling S. aureus infection. It can be prevented by adhering to appropriate housing and milking technologies, more frequent fly extermination, pre- and post-disinfection of the teats, the use of disposable udder wipers and regular laboratory testing [18].

External and internal factors can affect the composition of milk, as well as the microbiological state of raw milk. The latter is mostly determined by the hygienic condition of the surfaces that come into direct contact with the milk [19]. Research by Peles et al. found that different husbandry and milking methods at dairy farms with different cow numbers had influencing effects on the microbiological quality of milk [20]. Tessema sought to find a correlation between breed, the age of the animals, the number of lactations and the stage of lactation, as well as the likelihood of S. aureus occurrence.

In his study, he found a significant difference in the prevalence of S. aureus in milk for the two cattle species studied. S. aureus was found in higher proportion of crossbred cows and in older individuals [21]. Examining the milk of different varieties, Bytyqi et al. found no difference in the colony counts obtained [22].

Although fewer Hungarian studies have been conducted on the subject, several international publication have examined whether the number of lactations and the stage of lactation have an influence on the daily milk volume of the animals, the composition of the milk and its microbiological parameters. According to Tessema, there is a significant difference in the prevalence of S. aureus, depending on how many lactations the animals have been through. In his study, he found that S. aureus was more common in the milk of cows that had calved more than twice and produced a positive California Mastitis Test [21]. Tenhagen et al. also found that the incidence of S. aureus increases with the age of the animals [23]. This may be related to the fact that the milking machine may damage the teats during milking, allowing microorganisms to enter the udder from the environment [24]. Another possible reason is that the health status of dairy animals may deteriorate with advancing age, which may have an adverse effect on the somatic cell count of milk [25].

The objective of our study was to determine at a Hungarian large-scale dairy farm whether there is a difference in the daily milk yield of primiparous and multiparous cows, as well as cows at different stages of lactation, and also in the composition (fat and protein content) and microbiological parameters (somatic cell count, total plate count, coliform and S. aureus count) of primiparous and multiparous cows, as well as cows at different stages of lactation.

3. Materials and methods

3.1. Place and time of sampling

A dairy farm in Hajdú-Bihar county (Hungary) was the site of our studies. 440–450 Holstein-Friesian cows are milked on the farm. The farm uses deep litter livestock-keeping and monodiet feeding. Milking takes place in a milking parlor, and no post-disinfection is carried out after milking.

The data on the daily amount of milk, fat and protein content and somatic cell count used for the calculations are derived from the milking results, i.e., from the examination results of the milk samples collected monthly by the Állattenyésztési Teljesítményvizsgáló Kft. All milking results of 38 individuals between May 2015 and January 2020 were used in the calculations. During the calculations, data on the first lactation of the cows (n=387), data on the 2nd to 5th lactation of the cows (n=446), as well as data on the early (under 100 days; n=275), middle (100 to 200 days; n=249) and late (over 200 days; n=309) stages of the lactation of the cows were summarized for the abovementioned time period.

Microbiological tests were performed between May 2018 and October 2019. A total of 62 milk samples were taken from 38 randomly selected, clinically healthy individuals for the microbiological tests. According to which lactation cycle the animals were in and in which stage of lactation during the sampling, the samples taken from the individual cows were classified as follows: 26 samples were taken from 15 primiparous cows and 36 samples were taken from 23 multiparous (2 to 5 calvings) Holstein-Friesian cows. Of the total 62 samples taken, 23 were taken in the early stage of lactation, 21 samples in the middle stage of lactation and 18 samples were taken from cows in the late stage of lactation.

Following pre-disinfection of the teats, wiping them dry using paper towels and milking of the first milk jets, samples were taken from all four udder quarters into sealable sterile plastic sampling vessels with a capacity of 50 ml. The vessels were transported in coolers to the microbiology laboratory of the Institute of Food Science of the University of Debrecen within two hours of sampling. Samples were processed within 24 hours of sampling.

3.2. Microbiological tests

Preparation of the milk samples and the subsequent microbiological tests were performed according to the procedure described by Petróczki et al. [26]. Sample preparation was carried out according to standard MSZ EN ISO 6887-1:2017 [27], the samples were stored at 4 °C until the beginning of the analysis, and they were homogenized by shaking before processing. To prepare the dilution series, peptone water was used which was prepared by dissolving 8.5 g of sodium chloride (VWR International Kft., Hungary) and 1.0 g of peptone (Merck Kft., Hungary) in 1,000 ml of distilled water.

After weighing the appropriate amounts (9 ml each) into test tubes, the diluent was sterilized in a pressure cooker at 120 °C for 30 minutes, then it was cooled and the decimal dilution series was prepared.

The total plate count was determined according to standard MSZ EN ISO 4833-1:2014 [28], which prescribes the use of a tryptone-glucose-yeast agar (Plate Count Agar, PCA) culture medium (Biolab Zrt., Hungary) supplemented with milk powder. After performing the prescribed plate casting method, the plates were incubated at 30 °C for 72 hours.

The amount of coliform bacteria was determined by the plate casting method according to standard ISO 4832:2006 [29], using sterile crystal violet-bile-lactose agar (Violet Red Bile Lactose, VRBL, Biolab Zrt., Hungary). The incubation period was 24 hours at 30 °C.

The determination of S. aureus was performed according to standard MSZ EN ISO 6888-1:2008 [30] by the spreading method, for which Baird-Parker agar (BPA, Biolab Zrt., Hungary) supplemented with egg yolk-tellurite emulsion (LAB-KA Kft., Hungary). The incubation period was 48 hours at 37 °C. S. aureus was isolated from other Staphylococcus species using a latex agglutination test (Prolex Staph Xtra Kit, Ferol Kft., Hungary).

3.3. Statistical analysis

For the analysis of our experimental results, for the calculation of descriptive statistics, for the logarithmic transformation of the amount of microorganisms and for performing t-tests and analysis of variance, the SPSS v.22.0 [31] software was used.

In the case of lactation number, variables were compared using unpaired t-tests and non-parametric Mann-Whitney tests, while in the case of lactation stage, the comparison was performed by one factor analysis of variance and non-parametric Kruskal-Wallis tests. Since the total plate count, the coliform count and the somatic cell count were not found to be normally distributed variables in several cases, a logarithmic transformation was used for these parameters. During statistical analyses, a value of P<0.05 was considered to indicate a significant difference.

4. Results

4.1. Effect of lactation number on milk yield, raw milk composition and its microbiological parameters

Mean and standard deviation values of the daily milk yield of primiparous and multiparous cows, as well as those of the fat and protein content, somatic cell count, total plate count, coliform and S. aureus count of the milk produced by them are shown in Table 1. Cows selected for the study were classified into groups based on the number of lactations (and calvings) into groups of primiparous and multiparous individuals. The average milk yield was 25.67 kg/day for primiparous cows, while in the case of multiparous cows it was 31.04 kg/day. The difference is significant (P<0.05), which means that our experiments confirmed the findings of Bondan et al. and Yang et al., that the daily amount of milk produced by multiparous cows is higher than that of primiparous cows [5, 32]. In the case of crossbred Holstein-Friesian cows, Gurmessa and Melaku studied, inter alia, the effect of calving number on milk yield, but found no difference between the daily milk yield of primiparous and multiparous cows [33]. Pratap and his research group also found no difference in the average daily milk yield of primiparous and multiparous cows (6.43±1.39 and 5.89±2.37 l/day, respectively) [34].

The average fat content of milk during the first lactation of cows selected during our research was 3.74±0.40%, while the average fat content of milk samples taken during the second or later lactation was 3.75±0.36%. The difference was not found to be significant (P>0.05). Similarly to our own results, no difference was found between the average fat content of the milk of primiparous and multiparous crossbred Holstein-Friesian cows by Gurmessa and Melaku, or Pratap et al. [33, 34]. On the other hand, it was found by Bondan and his group that the number of lactations did have an effect on the fat content of milk in Holstein-Friesian cows. While the fat content was 3.47±0.67% in the case of cows lactating for the first time, it was 3.43±0.68% and 3.41±0.67% for cows lactating for the 2nd or 3rd time and for cows that had calved at least 4 times, respectively [5]. In their study in Sudan, Shuiep and his working group examined changes in the fat content of milk with the number of lactations in local and crossbred cows. In the case of local cows, cows in their fourth lactation period had a lower milk fat content (4.82±0.55%) than cows with fewer calvings (1:5.16±0.32; 2:5.22±0.34; 3:5.14±0.34). No difference was observed in the case of crossbred cows [6]. In contrast, Yang et al. found in their research that Holstein-Friesian cows lactating for the first time had a lower milk fat content (3.88%) [32]. Based on the varied results of our study and other literature references, we came to the conclusion that the fat content of milk may be influenced by other factors besides the lactation number.

During the first lactation of the Holstein-Friesian cows selected by us, the average protein content of the milk was 3.24±0.19%, while the average protein content of milk samples taken during the second or later lactation was 3.31±0.16%, with the difference being not significant (P>0.05). This is in line with the findings of Gurmessa and Melaku, as well as those of Pratap et al., as these authors did not find any difference between the average protein content of the milk of primiparous and multiparous cows [33, 34]. In contrast, the research group of Bondan found that the lactation number affected the protein content of milk in Holstein-Friesian cows. While the protein content was 3.24±0.37% in the case of cows lactating for the first time, it was 3.23±0.38% and 3.19±0.37% in the case of cows lactating for the 2nd or 3rd time and for cows that had calved at least 4 times, respectively [5]. Changes in the protein content of milk with the lactation number was also studied by the research group of Shuiep. In the case of local cows, the protein content of milk was lower in the case of cows in their fourth lactation period (3.67±0.19%), than in the case of cows with fewer calvings (1:4.01±0.11; 2:3.82±0.12; 3:3.84±0.12). No difference was observed in crossbred cows [6].

According to our results, the average somatic cell count [242.2×103 (5.12±0.42 lg) cell/ml] in the milk of primiparous cows is less (P<0.05) then in the milk of multiparous cows [356.3×103 (5.39±0.39 lg) cell/ml]. In none of the cases did the averages exceed the limit value [M=400.0×103 (5.60 lg) cfu/ml] laid down in Regulation (EC) No 853/2004 [35]. The results obtained at the Hungarian dairy farm are in line with relevant literature data. According to Mikó et al., as the lactation number increases, the somatic cell count of milk may also increase [25]. This finding was also found to be true by Yang and his group [32]. Sheldrake et al. observed a significant relationship between the calving number and the somatic cell count. They found that with the increase in calving number, there was a smaller change in the udder quarters of healthy animals, however, in the case of udder quarters infected with S. aureus, the somatic cell count increased significantly [36]. The research team of Bondan found that as the lactation number of the Holstein cows studied increased, so did the somatic cell count in milk. While the average somatic cell count in primiparous cows was 4.83±1.73 lg cell/ml, it was 5.31±1.72 és 5.84±1.62 lg cell/ml in cows that had calved 2 or 3 times and cows that calved 4 or more times, respectively [5].

In the milk samples taken from Holstein-Friesian cows that only calved once, i.e., cows in their first lactation period, the average total plate count was 5.1×103 (3.36±0.58 lg) cfu/ml, while it was 4.6×103 (3.30±0.59 lg) cfu/ml in the milk samples taken from multiparous cows, however, the difference was not significant (P>0.05).

However, the average coliform count [1.1×103 (1.35±1.20 lg) cfu/ml] in the milk of multiparous cows was more (P<0.05) than the average coliform count [1.1×101 (0.65±0.61) lg) cfu/ml] measured in the milk of primiparous cows. Tenhagen et al. also included clinically healthy cows in their study, which found that although coliform bacteria were found in higher quantities in the milk of multiparous cows, the difference was not significant [23].

S. aureus was present in only one of the 26 milk samples taken from primiparous cows, in an amount of 5.0×101 (1.70 lg) cfu/ml, while it could be detected in eight of the 36 milk samples taken from multiparous cows. The mean S. aureus count in these samples was 1.5×102 (1.92±0.56 lg) cfu/ml. The values do not exceed the limit value [M=5.0×102 (2.70 lg) cfu/ml] specified by EüM decree 4/1998 (XI. 11.) [37]. In the case of the individuals in whose milk S. aureus could be detected during the microbiological tests, the average somatic cell count was between 44.3×103 (4.65 lg) cell/ml and 357.2×103 (5.55 lg) cell/ml on the basis of milking data. In his study, Tessema also found that the prevalence of S. aureus was higher in the case of multiparous cows (i.e., who had calved more than twice) (who produced a positive California Mastitis Test) [21]. According to Tenhagen et al., the incidence of S. aureus increases with the age and lactation stage of the animals [23].

Table 1. Milk yield of primiparous and multiparous cows and compositional and microbiological properties of milk collected from them

a, b The values marked with different letters in the same rows of the table differ significantly (P<0.05)

4.2. Effect of lactation stage on milk yield, raw milk composition and its microbiological parameters

Mean and standard deviation values of the daily milk yield of cows in the early, middle and late stages of lactation, as well as those of the fat and protein content, somatic cell count, total plate count, coliform and S. aureus count of the milk produced by them are shown in Table 2. The cows selected for the study were classified into groups of early, middle and late lactation stage individuals, based in their stage of lactation. When examining the changes in the daily milk yield of the individuals with the stage of lactation, the finding in the literature that the daily milk yield decreases towards the end of lactation was confirmed. While the average daily milk yield of cows in the early stage of their lactation was 32.10±4.73 kg/day, that of cows in the middle stage of their lactation was 29.08±5.09 kg/day, while that of cows in the late stage of lactation was 23.36±3.63 kg/day. The difference was significant (P<0.05). Bondan and his group came to a similar conclusion in their study. The average milk yield between days 6 and 60 of the lactation of the Holstein-Friesian cows studied by them was 29.4±8.72 l/cow/day; for cows between days 61 and 120 of their lactation, it was 29.2±8.66 l/cow/day; for cows between lactation days 121 and 220, the milk yield was 26.2±8.01 l/cow/day, and at the end of the lactation (>220 days), it was 22.0±7.49 l/cow/day [5]. Gurmessa and Melaku, as well as Pratap et al. also found that the daily milk yield of the animals was higher at the beginning of lactation (6.81±1.45 l/day) than at the end of lactation (5.48±0.05 l/day). In their studies, the daily milk yield of crossbred Holstein-Friesian cows in the middle stage of their lactation was the highest (7.17±0.05 liter) [33, 34]. According to Auldist et al., the effect of lactation stage on milk yield (e.g., a decrease) may be due to a change in the number and activity of the secretory cells within the mammary gland because of physiological reasons [2].

The fat content of the milk of the individuals studied shows a change as we progress towards the end of lactation. The average fat content of cows in the early and middle stages of lactation was 3.65±0.43% and 3.59±0.41%, respectively, which were lower (P<0.05) than the fat content of the milk of cows in the late stage of lactation (3.99±0.47%). The increase in milk fat concentration at the end of lactation may be associated with a decrease in milk yield as lactation progresses, as a decrease in milk yield may have a concentrating effect on milk composition [2]. The fat content of milk also varies at the three stages of lactation according to the publication of Gurmessa and Melaku. For cows in the early or late stages of lactation, the average fat content of the milk (4.46±1.44% and 4.46±1.44%, respectively) was significantly higher than that of cows in the middle stage of lactation (3.70±0.89%) [33]. The publication of Bondan et al. states that the fat content of milk at the end of lactation (>200 days) is higher (3.55±0.67%) than at earlier stages of lactation. However, they also found that the measured average fat content (3.30±0.66%) was lowest between days 61 and 120 of the lactation of the cows. Between days 6 and 60, and between days 121 and 220, average fat contents of 3.40±0.65% and 3.40±0.66% were measured, respectively [5]. Shuiep et al. studied changes in the fat content of milk of local and crossbred cows in Sudan with lactation stage. In the case of the local breed, there was no difference in the fat content between the early (5.31±0.51%), middle (4.67±1.56%) and late (5.28±0.75%) stages of lactation. However, in the case of crossbred cows, the fat content was higher at the end of lactation (4.45±1.43%) than at the beginning of the lactation (3.41±1.09%) or in the middle stage of lactation (3.33±1.05%) [6].

Similar to the fat content, a change in protein content can also be observed as we progress towards the end of lactation. The average protein content measured at the beginning of lactation was 3.08±0.15%, it was 3.20±0.19% in the middle of lactation and 3.56±0.20% at the end of lactation, the difference being significant (P<0.05). Bondan et al. came to a similar conclusion: a higher protein content (3.41±0.36%) was measured at the end of lactation (>200 days) than at earlier stages of lactation. It was also found that the measured average protein content (3.03±0.31%) was the lowest between days 61 and 120 of the lactation of the cows. The measured average protein content between days 6 and 60 of the lactation and between days 121 and 220 were 3.05±0.36% and 3.18±0.32%, respectively [5]. Gurmessa and Melaku, as well as the research group of Pratap did not find any difference in protein content between cows in the early (3.55±1.43%), middle (3.17±0.15%) and late (3.33±0.16%) stages of their lactation [33, 34]. In the case of local and crossbred cows in Sudan, changes in milk protein content with the lactation stage were investigated by Shuiep et al. In the case of the local breed, the protein content of the milk of the animals was higher at the beginning (3.87±0.52%) and in the middle (3.91±0.18%) of lactation than at the end of lactation (3.67±0.17%). In the case of crossbred cows, there was no difference in protein content at the beginning (3.67±0.17%), middle (3.69±0.16%) and end (3.63±0.22%) of lactation [6].

The average somatic cell count in the early stage of lactation of the cows selected for our research was 195.1×103 (5.07±0.43 lg) cell/ml, it was 370.6×103 (5.28±0.50 lg) cell/ml in the middle of lactation, and it was 336.4×103 (5.33±0.41 lg) cell/ml in the late stage of lactation. The somatic cell count was higher (P<0.05) in the milk of individuals in the late stage of lactation than in the case of cows at the beginning of lactation. As lactation progresses, somatic cell counts also show an increasing trend according to Bondan et al. While in the milk of Holstein-Friesian cows between days 6 and 60 of their lactation the average somatic cell count was 4.79±1.90 lg cell/ml, between days 61 and 120 it was 4.89±1.90 lg cell/ml, between days 121 and 220 it was 5.21±1.75 lg cell/ml, and in the case of lactations lasting more than 220 days, this parameter was 5.53±1.53 lg cell/ml in the milk of the cows studied [5].

Total plate counts were also determined during the different stages of lactation of Holstein-Friesian cows. At the beginning of lactation, the average total plate count was 6.8×103 (3.42±0.67 lg) cfu/ml, in the middle of lactation it was 4.4×103 (3.39±0.46 lg) cfu/ml, while at the end of lactation it was 2.7×103 (3.13±0.56 lg) cfu/ml. No significant difference was found between the total plate count values obtained (P>0.05).

Regarding the number of coliform bacteria, the highest count [1.3×103 (1.30±1.23 lg) cfu/ml] was measured in samples taken at the beginning of the lactation of the cows, while the lowest average coliform count [2.2×101 (0.76±0.79 lg) cfu/ml] was detected in samples taken in the middle stage of lactation. The average coliform count in the samples taken at the end of lactation was 1.50×102 (0.90±0.94 lg) cfu/ml. There was no significant difference between the results (P>0.05).

S. aureus was present in a total of 9 samples (14.52%) out of 62 individual milk samples, with an average count of 1.4×102 (1.89±0.53 lg) cfu/ml. In the six samples (9.68%) taken from cows in the early stage of lactation, the average S. aureus count was 1.2×102 (1.81±0.56 lg) cfu/ml, for the single animal in the middle of lactation (1.61%) the S. aureus count was 8.2×101 (1.91 lg) cfu/ml, while for the two cows at the end of lactation (3.23%) it was 2.4×102 (2.15±0.70 lg) cfu/ml.

Table 2. Milk yield of cows in their early, mid and late lactation stages and compositional and microbiological properties of milk from them

a, b, c The values marked with different letters in the same rows of the table differ significantly (P<0.05)

5. Conclusions

In the course of our research work in a Hungarian dairy farm, it was proven that, under large-scale husbandry conditions, for primiparous cows the average daily milk yield is significantly lower (P<0.05) than in the case of multiparous cows. This is probably due to the fact that cows in their first lactation need more amino acids and fat to develop their bodies compared to animals that have already undergone several lactation periods [38].

Regarding the fat and protein content of the milk, there was no significant difference between primiparous and multiparous cows. Since one can find in the literature findings that both support and contradict our results, we assume that the fat and protein contents of milk are also influenced by other factors (e.g., breed, season, etc.), but mapping out of these factors was not the objective of our study. For example, Shuiep et al. reported in their paper different results for two different cattle breeds when examining the changes in the fat and protein contents of milk with the lactation number [6].

Based on our measurement results, we found that the somatic cell count, as well as the coliform count and the S. aureus count were significantly higher (P<0.05) in the milk samples taken from multiparous cows compared to the milk samples taken from primiparous cows. The reason why microorganisms can be measured in larger amounts in milk samples taken from multiparous cows is probably that the teats may have been damaged during the lactations (due to, for example, the milking machine), which may have increased the chances of microorganisms entering the udder [24]. Another reason may be that as the age progressed or the number of lactations increased, the condition of the dairy animals may have deteriorated, which may have had an adverse effect, for example, on the somatic cell count of the milk [25].

It was also proven that, in the stages of lactation, a decreasing trend in daily milk yield can be observed, but the fat and protein contents show an increase. This is presumably due to the concentrating effect of the decreasing milk yield.

There was no difference in milk samples taken at different stages of lactation in terms of total plate count and coliform count, however, in the late stage of lactation, the somatic cell count showed an increase.

6. Acknowledgment

This publication was supported by the project EFOP-3.6.3-VEKOP-16-2017-00008. The project was supported by the European Union and co-financed by the European Social Fund.

We are grateful to the management and staff of the dairy farm for their helpful assistance.

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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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