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Tesi etd-02092016-152620


Tipo di tesi
Tesi di laurea magistrale
Autore
CONDINO, FRANCESCO
URN
etd-02092016-152620
Titolo
Strategie di Bioaugmentation microbico nel trattamento biologico di sedimenti di dragaggio contaminanti da idrocarburi pesanti
Dipartimento
BIOLOGIA
Corso di studi
BIOTECNOLOGIE MOLECOLARI E INDUSTRIALI
Relatori
relatore Prof. Lorenzi, Roberto
relatore Dott.ssa Di Gregorio, Simona
Parole chiave
  • Bioaugmentation
  • Biostimolation
  • Total Petroleum Hydrocarbons
Data inizio appello
29/02/2016
Consultabilità
Non consultabile
Data di rilascio
28/02/2086
Riassunto
Soil and sediments are a reservoir for organic and inorganic contaminants from industrial activities, air pollution, accidental spills, urban waste and other anthropogenic activities. The dredged sediments are often characterized by the presence of high concentrations of Total Petroleum Hydrocarbons (TPHs), a term used to describe a family of organic compounds from crude oil, which influences its relocation and disposal. Different methods of treatment can be used to reduce the level of contamination and, among the available technologies, sustainable strategies for bioremediation, such as biostimulation and/or bioaugmentation of autochthonous or allochtonous microbial communities, can be exploited. The present work is part of the project "Bio RESNOVA: Recovery and exploitation of contaminated soils and Sediments by innovative Biotechnologies supported by physical – chemical processes. In an effort to reach the target of the project, an innovative biotechnology experiment for the remediation of sediments contaminated by heavy hydrocarbons was set up. The proposed method aims at improving the established approaches of bio-stimulation of the indigenous bacterial community, by increasing the process success with mycoremediation protocols, based on the exploitation and optimization of fungal metabolism. The experimental design of the Bioresnova has required the preparation of laboratory scale mesocosms to verify the efficiency of the treatment for the biological decontamination of sediments. With this aim, lignocellulosic matrices were initially used as a "bio-active" bulking agent and as a vehicle of inoculum of an allochthonous fungal specie. In parallel, we proceeded to the isolation of indigenous fungal strains from sediments belonging to the phylum Ascomycetes. Their metabolic capabilities were studied and the most promising candidate in terms of degradative ability was massively inoculated into the matrix, allowing the complete removal of contamination in just 28 days of treatment. Despite this promising result, the toxicological assessment revealed residual genotoxicity into the treated matrix.
For this reason, we performed a detailed molecular characterization of nine bacterial candidates isolate from sediment, in order to exploit integrated bioaugmentation protocols taking advantage of the synergism between the fungal and bacterial metabolism, and in this way overcome issues both related to the contamination level and the residual toxicity.
Despite the bacterial morphotypes are referable to the Pseudomonas and Stenotrophomonas genera and within these genera to a single bacterial specie, the genotypic characterization via Repetitive Sequence-Based PCR analysis confirmed that each of the analyzed morphotypes belongs to a distinct strain.
The present work has therefore evaluated the possibility of using molecular markers, selected from structural and functional bacterial genes, to monitor the progress of the bioaugmentation process with bacteria.
PCR analysis of genes coding for an alkane hydroxylase involved in the degradation of the TPH saturated fraction, has suggested the presence of a new genotype of alkB gene in one of the candidates selected for the bacterial bioaugmentation.
The partial sequence in question proves to be a possible marker for monitoring the candidate vitality and degrading activity, since preliminary data show its sequence divergence with genotypes of putative genes coding for the alkane hydroxylase AlkB, both those identified in the analyzed matrix and those already-known and included into data banks.
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