The Interrelationship Between Microbiota and Peptides During Ripening as a Driver for Parmigiano Reggiano Cheese Quality

Abstract

Cheese microbiota contribute significantly to the final characteristics of cheeses due to the growth and interaction between cheese microorganisms during processing and ripening. For raw milk cheeses, such as Parmigiano Reggiano (PR), the microbiota derive from the raw milk itself, the dairy environment, and the starter. The process of cheese making and time of ripening shape this complex ecosystem through the selection of different species and biotypes that will drive the quality of the final product by performing functions of their metabolism such as proteolysis. The diversity in the final peptide and amino acid composition of the cheese is thus mostly linked to the diversity of this microbiota. The purpose of this study was to get more insight into the factors affecting PR cheese diversity and, more specifically, to evaluate whether the composition of the bacterial community of cheeses along with the specific peptide composition are more affected by the ripening times or by the cheese making process. To this end, the microbiota and the peptide fractions of 69 cheese samples (from curd to cheese ripened 24 months) were analyzed during 6 complete PR production cycles, which were performed in six different dairies located in the PR production area. The relation among microbial dynamics, peptide evolution, and ripening times were investigated in this unique and tightly controlled production and sampling set up. The study of microbial and peptide moieties in products from different dairies - from curd to at least 12 months, the earliest time from which the cheese can be sold, and up to a maximum of 24 months of ripening - highlighted the presence of differences between samples coming from different dairies, probably due to small differences in the cheese making process. Besides these differences, however, ripening time had by far the greatest impact on microbial dynamics and, consequently, on peptide composition.

Keywords: Parmigiano Reggiano; cheese microbiota; cheese peptides; cheese ripening; raw milk cheese.

FIGURE 1

A graphical representation of the sampling scheme. For each dairy (A–F), samples were taken from the same cheese making lot (same wheel, W) at different ripening stages, and from different cheese making lots (different wheels) at the same ripening stage. As an example, AW1/0 corresponds to dairy A, wheel 1, months of ripening 0, that is to say, the curd after 48 h from cheese-making; AW1/6 is the same wheel sampled after 6 months. Samples from the same cheese making lot are connected by arrows. The time of ripening is also indicated at the top of the picture by an arrow.

FIGURE 2

The relative abundance of OTUs based on 16S rRNA sequencing; only bacterial species present in at least two samples with an abundance above 1% are shown. Results are reported for dairies A to F, samples are named according to the scheme reported in section “Cheese Sampling.”

FIGURE 3

Microbial counts (MRS 42°C: SLAB; CA 37°C: NSLAB; Total cells, Viable Cells) during cheese ripening. For each ripening stage, the means of all the samples with same aging time are shown. Bars represent differences among samples from different dairies (standard errors). Significant differences (p < 0.05; ANOVA followed by Tukey post hoc test) as a function of the ripening time are indicated by different letters. The coloring of descriptive statistics corresponds with the colors of the variables. The viable and total counts were not significantly different.

FIGURE 4

The relative abundance of entire (indicated by _ent) and lysed (indicated by _lys) bacterial cells at different ripening stages. Ripening times are as follows: 0, curd samples, 1, 1 month samples; 2, 2 month samples; 7, 7 month samples; 6, 6 month samples; 9, 9 month samples,12, 12 month samples; 24, 24 month samples. Bacterial species are abbreviated as follows: Lh, L. helveticus; Ld, L. delbrueckii; St, S. thermophilus; Lf, L. fermentum; Lcg, Lacticaseibacillus (formerly L. casei group). Significant differences (p < 0.05; ANOVA followed by Tukey post hoc test) for each species, entire/lysed, as a function of the ripening time are indicated by different letters. The coloring of descriptive statistics corresponds with the colors of the variables. For samples that were statistically different from all the others, no letters were reported.

FIGURE 5

Diversity indices during cheese ripening determined by LH-PCR. Species were detected by comparing the amplicon lengths with the LH-PCR databases. For each ripening stage, the means of all the samples with same aging times are shown. Bars represent differences among samples from different dairies (standard errors). Simpson (D = Σ pi2); the Simpson’s index value is given as 1-D. pi is the relative abundance of a given LH-PCR peak; Richness (S) is equal to the number of species. Evenness (E) is the relative abundance with which each species is represented, [E = H/Hmax; were H is Shannon index (H = −Σ piln(pi)) and Hmax = lnS]. pi is the relative abundance of a given LH-PCR peak and is obtained by dividing the area of each peak with the total area of all peaks in the electropherogram profile for each sample. Significant differences (p < 0.05; ANOVA followed by Tukey post hoc test) as a function of the ripening time are indicated by different letters for each index. Simpson values were significantly different among all ripening stages, thus no letters were indicated.

FIGURE 6

The loading plot of the peptides semi-quantitative data colored according to the aging time: 48 h (yellow), 1–2months (blue), 6 months (red), 7–24 months (green).

FIGURE 7

A heat map showing Spearman’s correlation between cheese microbiota and peptides abundance. Rows and columns are clustered by Euclidean distance and Ward linkage hierarchical clustering. The intensity of the colors represents the degree of association, as measured by Spearman correlations. Only taxa occurring in at least 20% of the samples were included.

FIGURE 8

The biplot of the distribution of microbial species and peptides according to the aging times and colored according to marked groups.