Microbiome and resitome and foods of animal origin

To ensure food safety and to prevent food-borne illnesses, rapid and accurate detection of pathogenic agents is essential. It has already been demonstrated that shotgun metagenomic sequencing can be used to detect pathogens and their antibiotic resistance genes in food. In the studies presented in this thesis, the application shotgun metagenomic sequencing has been applied to investigate both the microbiome and resistome of foods of animal origin in order to assess advantages and disadvantages of shotgun metagenomic sequencing in comparison to the cultural methods. In the first study, it has been shown that shotgun metagenomics can be applied to detect microorganisms experimentally spiked in cold-smoked salmon. Nevertheless, a direct correlation between cell concentration of each spiked microorganism and number of corresponding reads cannot be established yet. In the second and third studies, the microbiomes and resistomes characterizing caeca and the corresponding carcasses of the birds reared in the conventional and antibiotic free farms were compared. The results highlighted the need to reduce sources of microbial contamination and antimicrobial resistance not only at the farm level but also at the post-harvest one. In the fourth study, it has been demonstrated that testing a single aliquot of a food homogenate is representative of the whole homogenate because biological replicates displayed overlapping taxonomic and functional composition. All in all, the results obtained confirmed that the application of shotgun metagenomic sequencing represents a powerful tool that can be used in the identification of both spoilage and pathogenic microorganism, and their resistome in foods of animal origin. However, a robust relationship between sequence read abundance and concentration of colony-forming unit must be still established.

Detection and Modeling of Boundary Layer Height

This thesis tackles the problem of the automated detection of the atmospheric boundary layer (BL) height, h, from aerosol lidar/ceilometer observations. A new method, the Bayesian Selective Method (BSM), is presented. It implements a Bayesian statistical inference procedure which combines in an statistically optimal way different sources of information. Firstly atmospheric stratification boundaries are located from discontinuities in the ceilometer back-scattered signal. The BSM then identifies the discontinuity edge that has the highest probability to effectively mark the BL height. Information from the contemporaneus physical boundary layer model simulations and a climatological dataset of BL height evolution are combined in the assimilation framework to assist this choice. The BSM algorithm has been tested for four months of continuous ceilometer measurements collected during the BASE:ALFA project and is shown to realistically diagnose the BL depth evolution in many different weather conditions. Then the BASE:ALFA dataset is used to investigate the boundary layer structure in stable conditions. Functions from the Obukhov similarity theory are used as regression curves to fit observed velocity and temperature profiles in the lower half of the stable boundary layer. Surface fluxes of heat and momentum are best-fitting parameters in this exercise and are compared with what measured by a sonic anemometer. The comparison shows remarkable discrepancies, more evident in cases for which the bulk Richardson number turns out to be quite large. This analysis supports earlier results, that surface turbulent fluxes are not the appropriate scaling parameters for profiles of mean quantities in very stable conditions. One of the practical consequences is that boundary layer height diagnostic formulations which mainly rely on surface fluxes are in disagreement to what obtained by inspecting co-located radiosounding profiles.

Investigating the role of Copy Number Variants in Specific Language Impairment and identification of new candidate genes

Specific language impairment (SLI) is a complex neurodevelopmental disorder defined as an unexpected failure to develop normal language abilities for no obvious reason. Copy number variants (CNVs) are an important source of variation in the susceptibility to neuropsychiatric disorders. Therefore, a CNV study within SLI families was performed to investigate the role of structural variants in SLI. Among the identified CNVs, we focused on CNVs on chromosome 15q11-q13, recurrently observed in neuropsychiatric conditions, and a homozygous exonic microdeletion in ZNF277. Since this microdeletion falls within the AUTS1 locus, a region linked to autism spectrum disorders (ASD), we investigated a potential role of ZNF277 in SLI and ASD. Frequency data and expression analysis of the ZNF277 microdeletion suggested that this variant may contribute to the risk of language impairments in a complex manner, that is independent of the autism risk previously described in this region. Moreover, we identified an affected individual with a dihydropyrimidine dehydrogenase (DPD) deficiency, caused by compound heterozygosity of two deleterious variants in the gene DPYD. Since DPYD represents a good candidate gene for both SLI and ASD, we investigated its involvement in the susceptibility to these two disorders, focusing on the splicing variant rs3918290, the most common mutation in the DPD deficiency. We observed a higher frequency of rs3918290 in SLI cases (1.2%), compared to controls (~0.6%), while no difference was observed in a large ASD cohort. DPYD mutation screening in 4 SLI and 7 ASD families carrying the splicing variant identified six known missense changes and a novel variant in the promoter region. These data suggest that the combined effect of the mutations identified in affected individuals may lead to an altered DPD activity and that rare variants in DPYD might contribute to a minority of cases, in conjunction with other genetic or non-genetic factors.

Relationships between plant diversity and environmental heterogeneity in rupicolous grasslands on gypsum. The case study of Alysso-Sedion albi (Habitat 6110).

Plant communities on weathered rock and outcrops are characterized by high values in species richness (Dengler 2006) and often persist on small and fragmented surfaces. Yet very few studies have examined the relationships between heterogeneity and plant diversity at small scales, in particular in poor-nutrient and low productive environment (Shmida and Wilson 1985, Lundholm 2003). In order to assess these relationships both in space and time in relationship, two different approaches were employed in the present study, in two gypsum outcrops of Northern Apennine. Diachronic and synchronic samplings from April 2012 to March 2013 were performed. A 50x50 cm plot was used in both samplings such as the sampling unit base. The diachronic survey aims to investigate seasonal patterning of plant diversity by the use of images analysis techniques integrated with field data and considering also seasonal climatic trend, the substrate quality and its variation in time. The purpose of the further, synchronic sampling was to describe plant diversity pattern as a function of the environmental heterogeneity meaning in substrate typologies, soil depth and topographic features. Results showed that responses of diversity pattern depend both on the resources availability, environmental heterogeneity and the manner in which the different taxonomic group access to them during the year. Species richness and Shannon diversity were positively affected by increasing in substrate heterogeneity. Furthermore a good turnover in seasonal species occurrence was detected. This vegetation may be described by the coexistence of three groups of species which created a gradient from early colonization stages, characterized by greater slope and predominance of bare rock, gradually to situation of more developed soil.

Fine Mapping of qroot-yield-1.06, a QTL for Root, Plant Vigor and Yield in Maize

Root-yield-1.06 is a major QTL affecting root system architecture (RSA) and other agronomic traits in maize. The effect of this QTL has been evaluated with the development of near isogenic lines (NILs) differing at the QTL position. The objective of this study was to fine map qroot-yield-1.06 by marker-assisted searching for chromosome recombinants in the QTL interval and concurrent root phenotyping in both controlled and field conditions, through successive generations. Complementary approaches such as QTL meta-analysis and RNA-seq were deployed in order to help prioritizing candidate genes within the QTL target region. Using a selected group of genotypes, field based root analysis by ‘shovelomics’ enabled to accurately collect RSA information of adult maize plants. Shovelomics combined with software-assisted root imaging analysis proved to be an informative and relatively highly automated phenotyping protocol. A QTL interval mapping was conducted using a segregating population at the seedling stage grown in controlled environment. Results enabled to narrow down the QTL interval and to identify new polymorphic markers for MAS in field experiments. A collection of homozygous recombinant NILs was developed by screening segregating populations with markers flanking qroot-yield-1.06. A first set of lines from this collection was phenotyped based on the adapted shovelomics protocol. QTL analysis based on these data highlighted an interval of 1.3 Mb as completely linked with the target QTL but, a larger safer interval of 4.1 Mb was selected for further investigations. QTL meta-analysis allows to synthetize information on root QTLs and two mQTLs were identified in the qroot-yield-1.06 interval. Trascriptomics analysis based on RNA-seq data of the two contrasting QTL-NILs, confirmed alternative haplotypes at chromosome bin 1.06. qroot-yield-1.06 has now been delimited to a 4.1-Mb interval, and thanks to the availability of additional untested homozygous recombinant NILs, the potentially achievable mapping resolution at qroot-yield-1.06 is c. 50 kb.