Food safety and zoonotic enteric pathogens: sources, risk factors and transmission routes of human salmonellosis and campylobacteriosis

Salmonella and Campylobacter are common causes of human gastroenteritis. Their epidemiology is complex and a multi-tiered approach to control is needed, taking into account the different reservoirs, pathways and risk factors. In this thesis, trends in human gastroenteritis and food-borne outbreak notifications in Italy were explored. Moreover, the improved sensitivity of two recently-implemented regional surveillance systems in Lombardy and Piedmont was evidenced, providing a basis for improving notification at the national level. Trends in human Salmonella serovars were explored: serovars Enteritidis and Infantis decreased, Typhimurium remained stable and 4,[5],12:i:-, Derby and Napoli increased, suggesting that sources of infection have changed over time. Attribution analysis identified pigs as the main source of human salmonellosis in Italy, accounting for 43–60% of infections, followed by Gallus gallus (18–34%). Attributions to pigs and Gallus gallus showed increasing and decreasing trends, respectively. Potential bias and sampling issues related to the use of non-local/non-recent multilocus sequence typing (MLST) data in Campylobacter jejuni/coli source attribution using the Asymmetric Island (AI) model were investigated. As MLST data become increasingly dissimilar with increasing geographical/temporal distance, attributions to sources not sampled close to human cases can be underestimated. A combined case-control and source attribution analysis was developed to investigate risk factors for human Campylobacter jejuni/coli infection of chicken, ruminant, environmental, pet and exotic origin in The Netherlands. Most infections (~87%) were attributed to chicken and cattle. Individuals infected from different reservoirs had different associated risk factors: chicken consumption increased the risk for chicken-attributed infections; animal contact, barbecuing, tripe consumption, and never/seldom chicken consumption increased that for ruminant-attributed infections; game consumption and attending swimming pools increased that for environment-attributed infections; and dog ownership increased that for environment- and pet-attributed infections. Person-to-person contacts around holiday periods were risk factors for infections with exotic strains, putatively introduced by returning travellers.

Epidemiological and functional characterization of Streptococcus pneumoniae pili

Streptococcus pneumoniae is an important life threatening human pathogen causing agent of invasive diseases such as otitis media, pneumonia, sepsis and meningitis, but is also a common inhabitant of the respiratory tract of children and healthy adults. Likewise most streptococci, S. pneumoniae decorates its surface with adhesive pili, composed of covalently linked subunits and involved in the attachment to epithelial cells and virulence. The pneumococcal pili are encoded by two genomic regions, pilus islet 1 (PI-1), and pilus islet-2 (PI-2), which are present in about 30% and 16% of the pneumococcal strains, respectively. PI-1 exists in three clonally related variants, whereas PI-2 is highly conserved. The presence of the islets does not correlate with the serotype of the strains, but with the genotype (as determined by Multi Locus Sequence Typing). The prevalence of PI-1 and PI-2 positive strains is similar in isolates from invasive disease and carriage. To better dissect a possible association between PIs presence and disease we evaluated the distribution of the two PIs in a panel of 113 acute otitis media (AOM) clinical isolates from Israel. PI-1 was present in 30.1% (N=34) of the isolates tested, and PI-2 in 7% (N=8). We found that 50% of the PI-1 positive isolates belonged to the international clones Spain9V-3 (ST156) and Taiwan19F-14 (ST236), and that PI-2 was not present in the absence of Pl-1. In conclusion, there was no correlation between PIs presence and AOM, and, in general, the observed differences in PIs prevalence are strictly dependent upon regional differences in the distribution of the clones. Finally, in the AOM collection the prevalence of PI-1 was higher among antibiotic resistant isolates, confirming previous indications obtained by the in silico analysis of the MLST database collection. Since the pilus-1 subunits were shown to confer protection in mouse models of infection both in active and passive immunization studies, and were regarded as potential candidates for a new generation of protein-based vaccines, the functional characterization was mainly focused on S. pneumoniae pilus -1 components. The pneumococcal pilus-1 is composed of three subunits, RrgA, RrgB and RrgC, each stabilized by intra-molecular isopeptide bonds and covalently polymerized by means of inter-molecular isopeptide bonds to form an extended fibre. The pilus shaft is a multimeric structure mainly composed by the RrgB backbone subunit. The minor ancillary proteins are located at the tip and at the base of the pilus, where they have been proposed to act as the major adhesin (RrgA) and as the pilus anchor (RrgC), respectively. RrgA is protective in in vivo mouse models, and exists in two variants (clades I and II). Mapping of the sequence variability onto the RrgA structure predicted from X-ray data showed that the diversity was restricted to the “head” of the protein, which contains the putative binding domains, whereas the elongated “stalk” was mostly conserved. To investigate whether this variability could influence the adhesive capacity of RrgA and to map the regions important for binding, two full-length protein variants and three recombinant RrgA portions were tested for adhesion to lung epithelial cells and to purified extracellular matrix (ECM) components. The two RrgA variants displayed similar binding abilities, whereas none of the recombinant fragments adhered at levels comparable to those of the full-length protein, suggesting that proper folding and structural arrangement are crucial to retain protein functionality. Furthermore, the two RrgA variants were shown to be cross-reactive in vitro and cross-protective in vivo in a murine model of passive immunization. Taken together, these data indicate that the region implicated in adhesion and the functional epitopes responsible for the protective ability of RrgA may be conserved and that the considerable level of variation found within the “head” domain of RrgA may have been generated by immunologic pressure without impairing the functional integrity of the pilus.

A clustering method for robust and reliable large scale functional and structural protein sequence annotation

Bioinformatics, in the last few decades, has played a fundamental role to give sense to the huge amount of data produced. Obtained the complete sequence of a genome, the major problem of knowing as much as possible of its coding regions, is crucial. Protein sequence annotation is challenging and, due to the size of the problem, only computational approaches can provide a feasible solution. As it has been recently pointed out by the Critical Assessment of Function Annotations (CAFA), most accurate methods are those based on the transfer-by-homology approach and the most incisive contribution is given by cross-genome comparisons. In the present thesis it is described a non-hierarchical sequence clustering method for protein automatic large-scale annotation, called “The Bologna Annotation Resource Plus” (BAR+). The method is based on an all-against-all alignment of more than 13 millions protein sequences characterized by a very stringent metric. BAR+ can safely transfer functional features (Gene Ontology and Pfam terms) inside clusters by means of a statistical validation, even in the case of multi-domain proteins. Within BAR+ clusters it is also possible to transfer the three dimensional structure (when a template is available). This is possible by the way of cluster-specific HMM profiles that can be used to calculate reliable template-to-target alignments even in the case of distantly related proteins (sequence identity < 30%). Other BAR+ based applications have been developed during my doctorate including the prediction of Magnesium binding sites in human proteins, the ABC transporters superfamily classification and the functional prediction (GO terms) of the CAFA targets. Remarkably, in the CAFA assessment, BAR+ placed among the ten most accurate methods. At present, as a web server for the functional and structural protein sequence annotation, BAR+ is freely available at http://bar.biocomp.unibo.it/bar2.0.

Differential expression analysis for sequence count data via mixtures of negative binomials

The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.