Lisete Sousa (CEAUL – FCUL)
Teresa Semedo (CIISA – FMVUL)
Tipo de bolsa
Bolsa de Investigação (BI)
Estado do projeto:
Cheese is a complex fermented dairy product, harbouring diverse microbial communities that change over time and vary depending on the type of cheese and production specifications.
This autochthonous microbiota plays a crucial role in determining flavour, quality and safety of the final product. Advances in OMIC methods, and the associated generation of big data, are renovating our understanding of cheese microbiology, enabling a clearer picture of this multifaceted ecology. To achieve a comprehensive characterization of the microbiota present in traditional cheese, this research project began by performing targeted and non-targeted metagenOMICs to samples being collected at Azeitão and Nisa, since 2016. This approach will allow characterizing the microbial community present in cheese, both technological microbiota and putative pathogens, providing a broader picture of this complex ecosystem.
Overall, data will be used to identify eco-specific features, able to act as fingerprints, which will be used to create traditional-cheese ID cards. Hence, OMICs profiling will betray the food origin, allowing authenticity and safety assessment, relevant for individual consumers and agri-food market.
- Comparison between cheese samples recovered from distinct regions, producers and years
of production, through the analysis of metagenOMICs data. Identification of discriminatory
features, which may be associated with specific samples, acting as cheese-ID cards
Síntese do Plano de Trabalho
During this study, metagenOMICs data obtained from one-hundred cheese samples (including replicates) will be compiled and organized for analysis using various statistical tools:
- (1) Evaluate differences within cheese samples, finding means that are significantly different from each other carrying out one-way analysis of variance (ANOVA) followed by the Tukey test, a single-step multiple comparison procedure;
- (2) Calculate Alpha and Beta diversity indices for microbiota by the qiime2R;
- (3) Find differences in microbiota among producers by Wilcoxon-Mann-Whitney test;
- (4) Study the relationships between microbial taxa abundance and metabolites Spearman’s correlations;
- (5) Find differences in microbial composition through ANOSIM (ANalysis Of SIMilarities), a non-parametric statistical test widely used in the field of ecology;
- (6) Compare the microbiota present in traditional Portuguese cheeses, produced in different years and regions of the country using methods for multivariate data analysis such as Factorial Analysis for Mixed Data.
Data generated will be used to create an OMIC-fingerprint – cheese ID card – for each year, region and/or producer, which may be used for product authentication (origin allocation). Nowadays, the cheese authenticity assessment is based on conventional microbiological and
chemical procedures, followed by sensorial analyses performed by trained panels. These approaches are known to be error-prone, substitution by more objective methodologies, although associated with higher costs and the need for trained personnel, can be a valid
alternative to prove authenticity of value-added products, such as traditional ewe’s cheese, especially considering high demand international markets.