De Filippis, Francesca (2015) The microbiome in dairy products assessed by metagenomics and metatranscriptomics. [Tesi di dottorato]

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Item Type: Tesi di dottorato
Lingua: English
Title: The microbiome in dairy products assessed by metagenomics and metatranscriptomics
Creators:
CreatorsEmail
De Filippis, Francescafrancesca.defilippis@unina.it
Date: 31 March 2015
Number of Pages: 149
Institution: Università degli Studi di Napoli Federico II
Department: Agraria
Scuola di dottorato: Scienze agrarie e agroalimentari
Dottorato: Scienze e tecnologie delle produzioni agro-alimentari
Ciclo di dottorato: 27
Coordinatore del Corso di dottorato:
nomeemail
Barbieri, Giancarlobarbieri@unina.it
Tutor:
nomeemail
Ercolini, DaniloUNSPECIFIED
Date: 31 March 2015
Number of Pages: 149
Uncontrolled Keywords: dairy products; metagenomics; food microbiome; metatranscriptomics
Settori scientifico-disciplinari del MIUR: Area 07 - Scienze agrarie e veterinarie > AGR/16 - Microbiologia agraria
Aree tematiche (7° programma Quadro): BIOTECNOLOGIE, PRODOTTI ALIMENTARI E AGRICOLTURA > "Fork to farm" - Prodotti alimentari (inclusi prodotti ittici), salute e benessere
Date Deposited: 07 Apr 2015 08:00
Last Modified: 15 May 2018 01:00
URI: http://www.fedoa.unina.it/id/eprint/10075
DOI: 10.6093/UNINA/FEDOA/10075

Abstract

Cheese is a biologically and biochemically dynamic food containing microorganisms both deliberately added as starters and non-starter adventitious contaminants. The microbiota present in cheese is complex and its growth and activity represent the most important, but the least controllable steps. During manufacturing and ripening, the microbiota is in continuous evolution, driven by the changes in the environmental conditions. Studies of the cheese microbiota can address several questions that are important for the improvement of dairy production and the monitoring of microbial species during manufacture and ripening can give important insights to understand process dynamics and work out conditions that can assure a premium quality. However, the methodological approach to study the microbiota has changed and microbial species and strains can be identified and monitored with higher levels of speed, reliability and sensitivity.The aim of the present thesis was the study of microbial diversity and dynamics of microorganisms involved in the cheese manufacturing and ripening processes by using a new culture-independent high-throughput sequencing (HTS) approach. Thus, different ecosystems were investigated in order to comprehend the specific role played by microorganisms in each cheese manufacture and in each step of cheese production. Very different cheese productions were taken into account: fresh and medium-ripened pasta-filata cheeses (Mozzarella and Caciocavallo Silano) and long-ripened cheeses (Grana Padano, Parmigiano Reggiano). Moreover, a novel approach for a sequencing-based strain monitoring of Streptococcus thermophilus was evaluated, through sequencing of the species-specific lacS gene amplicons. Finally, the application of shotgun metatranscriptome sequencing was firstly investigated for the monitoring of microbial gene expression during cheese manufacturing and ripening. Overall, thanks to the different HTS approaches it was possible to obtain a complete picture of the microbiome involved in each dairy production. In most of the cheese manufactures, a naturally-selected core microbiome was found in both the fermentation and the ripening phases, including few species well-adapted to the dairy environment. Curd fermentation is mainly driven by few thermophilic lactic acid bacteria (LAB), while mesophilic non-starter LAB take over during the ripening. The evolution of the microbiota and its activities during ripening are strictly dependent on the environmental conditions and can be shaped through the modulation of the technological parameters applied. The application of shotgun metatranscriptome allowed the identification and quantification of microbial key genes involved in cheese ripening. Finally, the HTS-based strain-monitoring has been shown to be a promising application, if genes highly variable within a species are selected. Understanding microbial behavior during cheese manufacturing is a pivotal step in order to ensure safety and quality in dairy productions. In this context, HTS allows an unprecedented in-depth analysis of the microbial consortia in dairy environments.

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