An assessment of factors characterising the microbiology of Grana Trentino cheese, a Grana-type cheese

Cultivable microbial diversity, peptide profiles, and bio-functional properties in Parmigiano Reggiano cheese

Introduction

Lactic acid bacteria (LAB) communities shape the sensorial and functional properties of artisanal hard-cooked and long-ripened cheeses made with raw bovine milk like Parmigiano Reggiano (PR) cheese. While patterns of microbial evolution have been well studied in PR cheese, there is a lack of information about how this microbial diversity affects the metabolic and functional properties of PR cheese.

Methods

To fill this information gap, we characterized the cultivable fraction of natural whey starter (NWS) and PR cheeses at different ripening times, both at the species and strain level, and investigated the possible correlation between microbial composition and the evolution of peptide profiles over cheese ripening.

Results and discussion

The results showed that NWS was a complex community of several biotypes belonging to a few species, namely, Streptococcus thermophilus, Lactobacillus helveticus, and Lactobacillus delbrueckii subsp. lactis. A new species-specific PCR assay was successful in discriminating the cheese-associated species Lacticaseibacillus casei, Lacticaseibacillus paracasei, Lacticaseibacillus rhamnosus, and Lacticaseibacillus zeae. Based on the resolved patterns of species and biotype distribution, Lcb. paracasei and Lcb. zeae were most frequently isolated after 24 and 30 months of ripening, while the number of biotypes was inversely related to the ripening time. Peptidomics analysis revealed more than 520 peptides in cheese samples. To the best of our knowledge, this is the most comprehensive survey of peptides in PR cheese. Most of them were from β-caseins, which represent the best substrate for LAB cell-envelope proteases. The abundance of peptides from β-casein 38-88 region continuously increased during ripening. Remarkably, this region contains precursors for the anti-hypertensive lactotripeptides VPP and IPP, as well as for β-casomorphins. We found that the ripening time strongly affects bioactive peptide profiles and that the occurrence of Lcb. zeae species is positively linked to the incidence of eight anti-hypertensive peptides. This result highlighted how the presence of specific LAB species is likely a pivotal factor in determining PR functional properties.

In Vivo Functional Properties of Dairy Bacteria

This literature review aimed to collect investigations on the in vivo evidence for bacteria associated with fermented dairy foods to behave as probiotics with beneficial effects in the prevention and treatment of various diseases. All main bacterial groups commonly present in high numbers in fermented milks or cheeses were taken into account, namely starter lactic acid bacteria (SLAB) Lactobacillus delbrueckii subsp. bulgaricus and lactis, L. helveticus, Lactococcus lactis, Streptococcus thermophilus, non-starter LAB (NSLAB) Lacticaseibacillus spp., Lactiplantibacillus plantarum, dairy propionibacteria, and other less frequently encountered species. Only studies regarding strains of proven dairy origin were considered. Studies in animal models and clinical studies showed that dairy bacteria ameliorate symptoms of inflammatory bowel disease (IBD), mucositis, metabolic syndrome, aging and oxidative stress, cancer, bone diseases, atopic dermatitis, allergies, infections and damage caused by pollutants, mild stress, and depression. Immunomodulation and changes in the intestinal microbiota were the mechanisms most often involved in the observed effects. The results of the studies considered indicated that milk and dairy products are a rich source of beneficial bacteria that should be further exploited to the advantage of human and animal health.

The Microbiota of Grana Padano Cheese. A Review

Grana Padano (GP) is the most appreciated and marketed cheese with Protected Designation of Origin in the world. The use of raw milk, the addition of undefined cultures (defined as 'sieroinnesto naturale'), the peculiar manufacturing proces, and the long ripening make the cheese microbiota play a decisive role in defining the quality and the organoleptic properties of the product. The knowledge on the microbial diversity associated with GP has been the subject, in recent years, of several studies aimed at understanding its composition and characteristics in order, on the one hand, to improve its technological performances and, on the other hand, to indirectly enhance the nutritional quality of the product. This review aims to briefly illustrate the main available knowledge on the composition and properties of the GP microbiota, inferred from dozens of studies carried out by both classical microbiology techniques and metagenomic analysis. The paper will essentially, but not exclusively, be focused on the lactic acid bacteria (LAB) derived from starter (SLAB) and the non-starter bacteria, both lactic (NSLAB) and non-lactic, of milk origin.

Raw Milk Microbiota Modifications as Affected by Chlorine Usage for Cleaning Procedures: The Trentingrana PDO Case

Milk microbiota represents a key point in raw milk cheese production and contributes to the development of typical flavor and texture for each type of cheese. The aim of the present study was to evaluate the influence of chlorine products usage for cleaning and sanitizing the milking equipment on (i) raw milk microbiota; (ii) the deriving whey-starter microbiota; and (iii) Trentingrana Protected Designation of Origin (PDO) cheese microbiota and volatilome. Milk samples from three farms affiliated to a Trentingrana PDO cheese factory were collected three times per week during a 6-weeks period in which a sodium hypochlorite detergent (period C) was used and during a subsequent 6-weeks period of non-chlorine detergent usage (period NC). Samples were subjected to microbiological [Standard Plate Count; coliforms; coagulase-positive staphylococci; and lactic acid bacteria (LAB)] and metagenomic analysis (amplification of V3-V4 regions of 16S rRNA gene performed on Illumina MiSeq platform). In addition, cheese volatilome was determined by SPME-GC-MS. In the transition from period C to period NC, higher SPC and LAB counts in milk were recorded. Milk metagenomic analysis showed a peculiar distinctive microbiota composition for the three farms during the whole experimental period. Moreover, differences were highlighted comparing C and NC periods in each farm. A difference in microbial population related to chlorine usage in bulk milk and vat samples was evidenced. Moreover, chlorine utilization at farm level was found to affect the whey-starter population: the usually predominant Lactobacillus helveticus was significantly reduced during NC period, whereas Lactobacillus delbrueckii had the exact opposite trend. Alpha- and beta-diversity revealed a separation between the two treatment periods with a higher presence of L. helveticus, L. delbrueckii, and Streptococcus thermophilus in cheese samples after NC detergent period. Cheese volatilome analysis showed a slight decrease in lipolysis during C period in the inner part of the cheese wheel. Although preliminary, these results suggest a profound influence on milk and cheese microbiota, as well as on raw milk cheese production and quality, due to the use of chlorine. However, further studies will be needed to better understand the complex relationship between chlorine and microbiota along all the cheese production steps.

Evaluation of bacterial communities of Grana Padano cheese by DNA metabarcoding and DNA fingerprinting analysis

The composition of the bacterial community of Grana Padano (GP) cheese was evaluated by an amplicon-based metagenomic approach (DNA metabarcoding) and RAPD-PCR fingerprinting. One hundred eighteen cheeses, which included 118 dairies located in the production area of GP, were collected. Two hundred fifty-four OTUs were detected, of which 82 were further discriminated between dominant (32 OTUs; > 1% total reads) and subdominant (50 OTUs; between 0.1% and 1% total reads) taxa. Lactobacillus (L.) delbrueckii, Lacticaseibacillus (Lact.) rhamnosus, Lact. casei, Limosilactobacillus fermentum, Lactococcus (Lc.) raffinolactis, L. helveticus, Streptococcus thermophilus, and Lc. lactis were the major dominant taxa ('core microbiota'). The origin of samples significantly impacted on both richness, evenness, and the relative abundance of bacterial species, with peculiar pattern distribution among the five GP production regions. A differential analysis allowed to find bacterial species significantly associated with specific region pairings. The analysis of pattern similarity among RAPD-PCR profiles highlighted the presence of a 'core' community banding pattern present in all the GP samples, which was strictly associated with the core microbiota highlighted by DNA metabarcoding. A trend to group samples according to the five production regions was also observed. This study widened our knowledge on the bacterial composition and ecology of Grana Padano cheese.

Cultivable non-starter lactobacilli from ripened Parmigiano Reggiano cheeses with different salt content and their potential to release anti-hypertensive peptides

The impact of salt and fat intake on human health drives the consumer's attention towards dairy food with reduced salt and fat contents. How changes in salt and fat content modulate dairy LAB population and the associated proteolytic activities have been poorly studied. Here, non-starter LAB populations from 12 Parmigiano Reggiano (PR) cheeses (12-month ripened), clustered in low salt and fat content (LL-PR) and high salt and fat content (HH-PR) groups, were investigated and identified at specie-level with molecular assays. Lactobacillus rhamnosus was dominant in HH-PR samples, whereas Lactobacillus paracasei in LL-PR samples. (GTG)₅ rep-PCR analysis discriminated 11 and 12 biotypes for L. rhamnosus and L. paracasei isolates, respectively. Screening for proteolytic activity identified L. rhamnosus strains more proteolytic than L. paracasei, and, within L. rhamnosus species, HH-PR strains were generally more proteolytic than LL-PR strains. Two L. rhamnosus representatives, namely strain 0503 from LL-PR and strain 2006 from HH-PR, were functionally characterized in cow milk fermentation assay. HH-PR strain 2006 overcame LL-PR strain 0503 in acidification performance, leading to a fermented milk with higher angiotensin I-converting enzyme inhibitory and antioxidant activities. L. rhamnosus 2006 was more prone to release VPP, while L. rhamnosus 0503 released higher amount of IPP. This study provides evidences that salt/fat content affects NSLAB cultivable fraction and the associated proteolytic ability resulting in a complex occurrence of bioactive peptides featuring health-promoting properties.

How the Fewest Become the Greatest. L. casei's Impact on Long Ripened Cheeses

Members of the Lactobacillus casei group, including species classified currently as L. casei, L. paracasei, and L. rhamnosus, are among the most frequently found species in raw milk, hard cooked, long-ripened cheeses. Starting from very low numbers in raw milk, they become dominant in the cheese during ripening, selected by physical and chemical changes produced by cheese making and ripening. Their presence at different stages of cheese making and ripening is crucial in defining product features. For these reasons, the scientific community has been more and more interested in studying these “tiny but mighty microbes” and their implications during cheese making and ripening. The present paper reviews the current literature on the effect of L. casei in cheeses, with particular reference to the case of Parmigiano Reggiano and Grana Padano, two of the most famous PDO (Protected Designation of Origin) Italian cheeses. Recent advances regarding the selection of new wild strains able to persist until the end of ripening and carrying out slow but crucial activities resulting in specific aromatic features, are also presented.

Metagenomics of pasteurized and unpasteurized gouda cheese using targeted 16S rDNA sequencing

BACKGROUND

The microbiome of cheese is diverse, even within a variety. The metagenomics of cheese is dependent on a vast array of biotic and abiotic factors. Biotic factors include the population of microbiota and their resulting cellular metabolism. Abiotic factors, including the pH, water activity, fat, salt, and moisture content of the cheese matrix, as well as environmental conditions (temperature, humidity, and location of aging), influence the biotic factors. This study assessed the metagenomics of commercial Gouda cheese prepared using pasteurized or unpasteurized cow milk or pasteurized goat milk via 16S rDNA sequencing.

RESULTS

Results were analyzed and compared based on milk pasteurization and source, spatial variability (core, outer, and under the rind), and length of aging (2-4 up to 12-18 months). The dominant organisms in the Gouda cheeses, based on percentage of sequence reads identified at the family or genus levels, were Bacillaceae, Lactococcus, Lactobacillus, Streptococcus, and Staphylococcus. More genus- or family-level (e.g. Bacillaceae) identifications were observed in the Gouda cheeses prepared with unpasteurized cow milk (120) compared with those prepared with pasteurized cow milk (92). When assessing influence of spatial variability on the metagenomics of the cheese, more pronounced differences in bacterial genera were observed in the samples taken under the rind; Brachybacterium, Pseudoalteromonas, Yersinia, Klebsiella, and Weissella were only detected in these samples. Lastly, the aging length of the cheese greatly influenced the number of organisms observed. Twenty-seven additional genus-level identifications were observed in Gouda cheese aged for 12-18 months compared with cheese only aged 2-4 months.

CONCLUSIONS

Collectively, the results of this study are important in determining the typical microbiota associated with Gouda cheese and how the microbiome plays a role in safety and quality.

Development of a time-effective and highly specific quantitative real-time polymerase chain reaction assay for the identification of Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus thermophilus in artisanal raw cow’s milk cheese

The first objective of this work included the development of real-time polymerase chain reaction (RT-PCR) which is also known as quantitative polymerase chain reaction (qPCR) assays to quantify two species of lactic acid bacteria which play a very important role in cheese ripening: Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus thermophilus. The second objective was the comparison of qPCR and plate counts of these two species present in raw cow’s milk cheese samples during different stages of ripening. Thirty-three deoxyribonucleic acid (DNA) samples coming from seven different bacterial species, which were phylogenetically related or commonly isolated from raw milk and dairy products, were chosen as positive and negative controls. The qPCR assays showed a high quantification capacity characterised by their linearity (R2 > 0.998), PCR efficiencies which were within the range 78.0–90.0% for L. delbrueckii subsp. bulgaricus, and 93.6–100.5% for S. thermophilus, and quantification limit (103 gene copies/ml for L. delbrueckii subsp. bulgaricus and 10 gene copies/ml for S. thermophilus). The importance of our study is in the monitoring of changes in populations of L. delbrueckii subsp. bulgaricus and S. thermophilus contributing to cheese ripening using the newly designed qPCR assay.

A bioinformatics pipeline integrating predictive metagenomics profiling for the analysis of 16S rDNA/rRNA sequencing data originated from foods

The recent advances in molecular biology, such as the advent of next-generation sequencing (NGS) platforms, have paved the way to new exciting tools which rapidly transform food microbiology. Nowadays, NGS methods such as 16S rDNA/rRNA metagenomics or amplicon sequencing are used for the taxonomic profiling of the food microbial communities. Although 16S rDNA/rRNA NGS-based microbial data are not suited for the investigation of the functional potential of the identified operational taxonomic units as compared to shotgun metagenomics, advances in the bioinformatics discipline allow now the performance of such studies. In this paper, a bioinformatics workflow is described integrating predictive metagenomics profiling with specific application to food microbiology data. Bioinformatics tools pertinent to each sub-module of the pipeline are suggested as well. The published 16S rDNA/rRNA amplicon data originated from an Italian Grana-type cheese, using an NGS platform, was employed to demonstrate the predictive metagenomics profiling approach. The pipeline identified the microbial community and the changes that occurred in the microbial profile during manufacture of the food product studied (taxonomic profiling). The workflow also indicated significant changes in the functional profiling of the community. The tool may help to investigate the functional potential, alterations, and interactions of a microbial community. The proposed workflow may also find an application in the investigation of the ecology of foodborne pathogens encountered in various food products.

Microbiota of an Italian Grana-Like Cheese during Manufacture and Ripening, Unraveled by 16S rRNA-Based Approaches

The microbial ecology of cheese involves a rich and complex interaction between starter lactic acid bacteria and nonstarter lactic acid bacteria (NSLAB), mainly originating from raw milk and/or from the environment, that can contribute to the final characteristics of cheese. The aim of the present research was the exploration of the active microbiota by RNA-based approaches during the manufacturing and ripening of a Grana-like cheese. Reverse transcriptase PCR (RT-PCR)-denaturing gradient gel electrophoresis (DGGE) and RNA-based high-throughput sequencing were applied to profile microbial populations, while the enumeration of active bacteria was carried out by using quantitative PCR (qPCR). Three different cheese productions (named D, E, and F) collected in the same month from the same dairy plant were analyzed. The application of the qPCR protocol revealed the presence of 7 log CFU/ml of bacterial load in raw milk, while, during ripening, active bacterial populations ranged from <4 to 8 log CFU/ml. The natural whey starters used in the three productions showed the same microbiota composition, characterized by the presence of Lactobacillus helveticus and Lactobacillus delbrueckii Nevertheless, beta-diversity analysis of the 16S rRNA sequencing data and RT-PCR-DGGE showed a clear clustering of the samples according to the three productions, probably driven by the different milks used. Milk samples were found to be characterized by the presence of several contaminants, such as Propionibacterium acnes, Acidovorax, Acinetobacter, Pseudomonas, and NSLAB. The core genera of the starter tended to limit the development of the spoilage bacteria only in two of the three batches. This study underlines the influence of different factors that can affect the final microbiota composition of the artisanal cheese.

IMPORTANCE

This study highlights the importance of the quality of the raw milk in the production of a hard cheese. Independent from the use of a starter culture, raw milk with low microbiological quality can negatively affect the populations of lactic acid bacteria and, as a consequence, impact the quality of the final product due to metabolic processes associated with spoilage bacteria.

Traditional cheeses: rich and diverse microbiota with associated benefits

The risks and benefits of traditional cheeses, mainly raw milk cheeses, are rarely set out objectively, whence the recurrent confused debate over their pros and cons. This review starts by emphasizing the particularities of the microbiota in traditional cheeses. It then describes the sensory, hygiene, and possible health benefits associated with traditional cheeses. The microbial diversity underlying the benefits of raw milk cheese depends on both the milk microbiota and on traditional practices, including inoculation practices. Traditional know-how from farming to cheese processing helps to maintain both the richness of the microbiota in individual cheeses and the diversity between cheeses throughout processing. All in all more than 400 species of lactic acid bacteria, Gram and catalase-positive bacteria, Gram-negative bacteria, yeasts and moulds have been detected in raw milk. This biodiversity decreases in cheese cores, where a small number of lactic acid bacteria species are numerically dominant, but persists on the cheese surfaces, which harbour numerous species of bacteria, yeasts and moulds. Diversity between cheeses is due particularly to wide variations in the dynamics of the same species in different cheeses. Flavour is more intense and rich in raw milk cheeses than in processed ones. This is mainly because an abundant native microbiota can express in raw milk cheeses, which is not the case in cheeses made from pasteurized or microfiltered milk. Compared to commercial strains, indigenous lactic acid bacteria isolated from milk/cheese, and surface bacteria and yeasts isolated from traditional brines, were associated with more complex volatile profiles and higher scores for some sensorial attributes. The ability of traditional cheeses to combat pathogens is related more to native antipathogenic strains or microbial consortia than to natural non-microbial inhibitor(s) from milk. Quite different native microbiota can protect against Listeria monocytogenes in cheeses (in both core and surface) and on the wooden surfaces of traditional equipment. The inhibition seems to be associated with their qualitative and quantitative composition rather than with their degree of diversity. The inhibitory mechanisms are not well elucidated. Both cross-sectional and cohort studies have evidenced a strong association of raw-milk consumption with protection against allergic/atopic diseases; further studies are needed to determine whether such association extends to traditional raw-milk cheese consumption. In the future, the use of meta-omics methods should help to decipher how traditional cheese ecosystems form and function, opening the way to new methods of risk-benefit management from farm to ripened cheese.