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Goat cheese is an important element of the Mediterranean diet, appreciated for its health-promoting features and unique taste. A pivotal role in the development of these characteristics is attributed to the microbiota and its continuous remodeling over space and time. Nevertheless, no thorough study of the cheese-associated microbiota using two metaomics approaches has previously been conducted. Here, we employed 16S rRNA gene sequencing and metaproteomics to explore the microbiota of a typical raw goat milk cheese at various ripening timepoints and depths of the cheese wheel. The 16S rRNA gene-sequencing and metaproteomics results described a stable microbiota ecology across the selected ripening timepoints, providing evidence for the microbiologically driven fermentation of goat milk products. The important features of the microbiota harbored on the surface and in the core of the cheese mass were highlighted in both compositional and functional terms. We observed the rind microbiota struggling to maintain the biosafety of the cheese through competition mechanisms and/or by preventing the colonization of the cheese by pathobionts of animal or environmental origin. The core microbiota was focused on other biochemical processes, supporting its role in the development of both the health benefits and the pleasant gustatory nuances of goat cheese.

The study of microbiomes has gained in importance over the past few years and has led to the emergence of the fields of metagenomics, metatranscriptomics, and metaproteomics. While initially focused on the study of biodiversity within these communities, the emphasis has increasingly shifted to the study of (changes in) the complete set of functions available in these communities. A key tool to study this functional complement of a microbiome is Gene Ontology (GO) term analysis. However, comparing large sets of GO terms is not an easy task due to the deeply branched nature of GO, which limits the utility of exact term matching. To solve this problem, we here present MegaGO, a user-friendly tool that relies on semantic similarity between GO terms to compute the functional similarity between multiple data sets. MegaGO is high performing: Each set can contain thousands of GO terms, and results are calculated in a matter of seconds. MegaGO is available as a web application at https://megago.ugent.be and is installable via pip as a standalone command line tool and reusable software library. All code is open source under the MIT license and is available at https://github.com/MEGA-GO/.

Milk is a complex body fluid aimed at addressing the nutritional and defensive needs of the mammal's newborns. Harbored microbiota plays a pivotal role throughout the cheesemaking process and contributes to the development of flavor and texture typical of different type of cheeses. Understanding the dairy microbiota dynamics is of paramount importance for controlling the qualitative, sensorial and biosafety features of the dairy products. Although many studies investigated the contribution of single or few microorganisms, still there is some information lacking about microbial communities. The widespread of the omics platforms and bioinformatic tools enable the investigation of the cheese-associated microbial community in both phylogenetical and functional terms, highlighting the effects of the diverse cheesemaking variables. In this review, the most relevant literature is revised to provide an introduction of the milk- and cheese-associated microbiota, along with their structural and functional dynamics in relation to the diverse cheesemaking technologies and influencing variables. Also, we focus our attention on the latest omics technologies adopted in dairy microbiota investigation. Discussion on the key-steps and major drawbacks of each omics discipline is provided along with a collection of results from the latest research studies performed to unravel the fascinating world of the dairy-associated microbiota. SIGNIFICANCE: Understanding the milk- and cheese- associated microbial community is nowadays considered a key factor in the dairy industry, since it allows a comprehensive knowledge on how all phases of the cheesemaking process impact the harbored microflora; thus, predict the consequences in the finished products in terms of texture, organoleptic characteristics, palatability and biosafety. This review, collect the pioneering and milestones works so far performed in the field of dairy microbiota, and provide the basic guidance to whom approaching the cheese microbiota investigation by means of the latest omics technologies. Also, the review emphasizes the benefits and drawbacks of the omics disciplines, and underline how the integration of diverse omics sciences enhance a comprehensive depiction of the cheese microbiota. In turn, a better consciousness of the dairy microbiota might results in the application of improved starter cultures, cheesemaking practices and technologies; supporting a bio-safe and standardized production of cheese, with a strong economic benefit for both large-scale industries and local traditional dairy farms., (Crown Copyright © 2019. Published by Elsevier B.V. All rights reserved.)

Unlabelled: Grana Padano is a typical Italian Protected Designation of Origin (PDO) hard cheese largely consumed all over the world. The major problem during its production is represented by late blowing. Clostridia are gasogen bacteria responsible of the swelling during ripening, and they are partially counteracted by the use of egg white lysozyme as additive. In this work was applied, for the first time in cheese, a metaproteomic approach that identified the functional dynamics of microbial consortia in relation to the number of clostridial spores and lysozyme treatment using experimental samples of Grana Padano cheese. We used a combined custom BLAST+/MEGAN/STAMP approach to obtain a global taxonomic view associated to low and high clostridial spores cheese without and with lysozyme. Main differences were highlighted in the bacilli class. Functional analysis with SEED provided a deep view into several metabolic pathways, highlighting the subsystems "amino acid and derivatives" and "clustering-based subsystem" as the targeted subsystems during lysozyme treatment in the high spore group. In these subsystems, acetate kinase from clostridia was one of the main enzymes affected by the lysozyme treatment., Biological Significance: Metaproteomics is a very promising and useful technique in the control of food safety and quality, from fresh products until 'ready to eat' food. Tools able to identify at molecular level the dynamic fingerprinting of food microbiota could be of great help to improve food safety and quality., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Extra virgin olive oil (EVOO) is a mainstay of the Mediterranean diet with its excellent balance of fats and antioxidant bioactive compounds. Both the phenolic and lipid fractions of EVOO contain a variety of antioxidant and anticancer substances which might protect from the development of colorectal cancer (CRC). The function of the intestinal microbiome is essential for the integrity of the intestinal epithelium, being protective against pathogens and maintaining immunity. Indeed, dysbiosis of the microbiota alters the physiological functions of the organ, leading to the onset of different diseases including CRC. It is known that some factors, including diet, could deeply influence and modulate the colon microenvironment. Although coming from animal models, there is increasing evidence that a diet rich in EVOO is linked to a significant reduction in the diversity of gut microbiome (GM), causing a switch from predominant bacteria to a more protective group of bacteria. The potential beneficial effect of the EVOO compounds in the carcinogenesis of CRC is only partially known and further trials are needed in order to clarify this issue. With this narrative review, we aim at discussing the available evidence on the effect of olive oil consumption on GM in the prevention of CRC. [ABSTRACT FROM AUTHOR]