Application of integrative multi-omics approaches to assess cheese quality and authenticity, and the effect of cheese consumption on gut microbiota
Creators: name: AFSHARI, Roya
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 300602
subject: Food chemistry and food sensory science

description: Complex interactions between cheese microbiota, their metabolites and milk substrates determine final cheese quality and flavour characteristics. Recent advances in metagenomics and metabolomics platforms offer new ways to assess the microbial composition and chemical diversity in cheese in greater detail. However, there is a need to go beyond determining just the microbial community structure or metabolite profiles individually, and instead focus on the inter-relationships and interactions between these and how they impact on cheese ripening outcomes. This can be achieved through the application of multi-omics combined with data integration analysis. This represents a new approach that has not yet, to our knowledge, been applied to food (including cheese) research. The application of high-throughput DNA and RNA sequencing technologies has further transformed our understanding of how diet influences the gut microbiota structure and function. In this regard, only very few studies to date have focused on the impact of cheese consumption as part of the regular human diet on the gut microbiota. Therefore, the aim of the research presented in this thesis was to gain deeper insights into the cheese (cheddar) microbiota and metabolome and explore the inter-relationships between them using multi-omics combined with data integration techniques, and to determine whether the discriminatory microbe and/or metabolite biomarker panels identified could be used to monitor cheese quality, and verify cheese ripening age, brand and product authenticity. A further goal was to determine the impact of regular consumption of cheddar cheese on gut microbiota in healthy human subjects.
 
Four research studies were conducted. In all studies, microbiota profiles were determined by 16S rRNA amplicon sequencing following total DNA extraction and the metabolome was analysed using GC-MS and/or LC-MS untargeted metabolomics. Methods used for integration of multi-omics datasets varied between studies. In Study 1, the microbiota composition and metabolome of different brands of artisanal and industrial cheddar cheeses were compared with multi-omics datasets integrated by MCIA. The results showed that Streptococcus, Lactococcus and Lactobacillus were the dominant genera in these cheeses with Streptococcus (presumably S. thermophilus) being dominant in the artisanal cheeses and Lactococcus (presumably L. lactis) and Lactobacillus in the industrial cheeses. Untargeted metabolomics analyses showed differences between the industrial and artisanal cheeses. This included two compounds (3-hydroxy propanoic acid and O-methoxycatechol-O-sulphate) in the artisanal cheeses that have not been previously reported in any food. Furthermore, these analyses revealed previously unknown associations between specific taxa and metabolites, such as relationships between low abundant taxa (Pediococcus) and 21 metabolites.

In Study 2, microbiota and metabolite profiles of retail industrial cheddar cheeses of different ripening ages (labelled as `mild', `tasty', `extra-tasty', or other similar names) made by different manufacturers (brands A, B and C) were analysed. Multi-omics analyses enabled explicit differentiation of similar brands of cheeses, and of cheeses of different ripening ages. Age-specific markers including numerous amino acids and carboxylic acids, such as malic acid, hydroxy-glutaric acid, citric acid, lauric acid, myristic acid, pentadecanoic acid and hexadecenoic acid, were found to be positively associated with the ripening age. In addition, integration and Random Forest regression analysis pinpointed several significant associations between the bacterial taxa and metabolites in these cheeses. These included a positive association between Thermus and phenylalanine that had not been previously reported and a negative association between Streptococcus and cholesterol. 

In Study 3, two similar-style cheddar cheeses of different qualities made by the same manufacturer were investigated in an attempt to identify microbiota and/or metabolite signatures (biomarkers) that could be used to assess cheese quality. Data integration was performed in a supervised manner using DIABLO. This led to the discovery of highly- correlated discriminatory biomarkers associated with cheese quality. These included Streptococcus species (presumably S. thermophilus), proline, histidine isoleucine and aspartic acid which were present in higher abundance in the high-quality cheeses, and Lactococcus lactis, stearic acid and octadecanol which were present in higher abundance in the low-quality cheeses. This suggests multi-omics combined with data integration is an effective approach for identifying biomarkers of cheese quality, although further work on this is needed. 

In Study 4, the effects of artisanal versus industrial cheddar cheese consumption on gut microbiota in healthy free-living human subjects were investigated. This dietary intervention trial was a randomised, double-blind, parallel-arm study in which participants consumed either artisanal or industrial cheese (50 g/day) for a consecutive two-week period followed by a one- week washout period. Analysis of stool microbiota at the beginning of the trial (baseline; BL) showed that participants could be clustered into two distinct 'enterotypes', either a Prevotella-or Bacteroides-dominated enterotype. During the course of the entire study, these enterotypes remained relatively stable. Consumption of artisanal cheeses for two weeks resulted in an increase in the relative abundance of Veillonacaea and some other butyrogenic bacteria such as Intestiminomas and Lachnospiraceae and a decrease in Hungatella. In contrast, consumption of industrial cheeses showed no significant effect on microbiota composition. This suggests that consumption of artisanal cheese is effective in modulating the gut microbiota composition compared with industrial cheese, possibly due to the greater diversity of microbiota in the artisanal cheeses (see Study 1).

The research presented in this thesis shows that multi-omics together with data integration analysis represents a powerful new approach for gaining deeper insights into the microbiota-metabolite interactions that underpin cheese flavour and quality. This approach has not been widely used in food research, and in this study lead to the discovery of biomarker panels that could be used to distinguish cheddar cheeses of different types (artisanal vs. industrial), different brands, and different qualities. Numerous significant associations between the microbiota and metabolites were uncovered including some not previously reported. These new associations provide a basis for further targeted studies examining the link between microbiota and metabolites and their role in cheese ripening and in determining cheese quality outcomes. The knowledge obtained from these studies could be applied to improve cheese grading practices and for verifying cheese brand and product authenticity. Dietary intervention studies showed that consumption of artisanal cheese leads to modulation of the gut microbiota composition in healthy adults.