Soverini, Matteo
(2020)
HOLOBIOMICS - Use of microbiomics for the exploration of microbial communities in holobionts., [Dissertation thesis], Alma Mater Studiorum Università di Bologna.
Dottorato di ricerca in
Scienze biotecnologiche e farmaceutiche, 32 Ciclo. DOI 10.6092/unibo/amsdottorato/9162.
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Abstract
Introducing more than a decade ago the High-Throughput Sequencing techniques we have exponentially increased our opportunities of shedding light on complex microbial communities. This revolution opened a ‘golden era’ in the new-born field of microbiomics, avoiding the culturing step that always represented a limiting factor in the characterization of particular and fastidious groups of microorganisms. Furthermore, it is clear the advantage of retrieving all the taxonomic and functional information encoded within a microbiome directly by sequencing a sample deriving from an environment of interest. The huge amount of information produced in studies relying on NGS represents a challenging task, constituting the main driver for the creation of the computational microbiologist: a new figure alongside the molecular microbiologist and classic microbiologist. This researcher’s work starts when the laboratory work ends and the sequencing process is completed: the aim of a computational microbiologist work is to deal with the vast amount of data generated by the sequencing process, producing biologically meaningful data. During my PhD I have focused on these latter tasks, dealing with the characterization at different levels of various holobionts, ranging from wild animals to humans, giving attention at the bacterial, fungal and viral fractions in ecosystems. In the present work I report the main achievements of my research work, whose common denominator is the bioinformatic approach to microbiome data. In the cases I studied, I observed a mutualistic microbiome that may follows adaptive strategies aimed at the conservation of the homeostasis of the total ecosystem. This work contributes to enrich the overall knowledge on the holobiont, also exploring some peculiar ecosystems for the first time. The data presented here may form the basis for future developments in the field, in order to obtain a more comprehensive profiling of bacterial, viral and fungal fractions within complex ecosystems.
Abstract
Introducing more than a decade ago the High-Throughput Sequencing techniques we have exponentially increased our opportunities of shedding light on complex microbial communities. This revolution opened a ‘golden era’ in the new-born field of microbiomics, avoiding the culturing step that always represented a limiting factor in the characterization of particular and fastidious groups of microorganisms. Furthermore, it is clear the advantage of retrieving all the taxonomic and functional information encoded within a microbiome directly by sequencing a sample deriving from an environment of interest. The huge amount of information produced in studies relying on NGS represents a challenging task, constituting the main driver for the creation of the computational microbiologist: a new figure alongside the molecular microbiologist and classic microbiologist. This researcher’s work starts when the laboratory work ends and the sequencing process is completed: the aim of a computational microbiologist work is to deal with the vast amount of data generated by the sequencing process, producing biologically meaningful data. During my PhD I have focused on these latter tasks, dealing with the characterization at different levels of various holobionts, ranging from wild animals to humans, giving attention at the bacterial, fungal and viral fractions in ecosystems. In the present work I report the main achievements of my research work, whose common denominator is the bioinformatic approach to microbiome data. In the cases I studied, I observed a mutualistic microbiome that may follows adaptive strategies aimed at the conservation of the homeostasis of the total ecosystem. This work contributes to enrich the overall knowledge on the holobiont, also exploring some peculiar ecosystems for the first time. The data presented here may form the basis for future developments in the field, in order to obtain a more comprehensive profiling of bacterial, viral and fungal fractions within complex ecosystems.
Tipologia del documento
Tesi di dottorato
Autore
Soverini, Matteo
Supervisore
Dottorato di ricerca
Ciclo
32
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Microbiome GutMicrobiota Bioinformatics Sequencing Holobiont
URN:NBN
DOI
10.6092/unibo/amsdottorato/9162
Data di discussione
3 Aprile 2020
URI
Altri metadati
Tipologia del documento
Tesi di dottorato
Autore
Soverini, Matteo
Supervisore
Dottorato di ricerca
Ciclo
32
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Microbiome GutMicrobiota Bioinformatics Sequencing Holobiont
URN:NBN
DOI
10.6092/unibo/amsdottorato/9162
Data di discussione
3 Aprile 2020
URI
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