Comparative Analysis of Genus Bifidobacterium: Insight into its Host Adaptation

Bifidobacteria is amongst one of the health promoting bacteria. The role of this important probiotic genera can be elucidated by understanding its genome. Comparative analysis of the whole genus of these bacteria can reveal their adaptation to a diverse host range. This study comprises of four research projects. In the first study, a reference library for genus Bifidobacterium was prepared. The core genes in each genus were selected based on a newly proposed statistical definition of core genome. Comparative analysis of Bifidobacterium with another probiotic genus Lactobacillus revealed the metabolic characteristics of genus Bifidobacterium. The second study investigated the immunomodulatory role of a B. bifidum strain TMC3115. The analysis of TMC3115 provided insights into its extracellular structures which might have their role in host interaction and immunomodulation. The study highlighted the variability among these genomes just not on species level but also on strain level in terms of host interaction. The last two studies aim to inspect the relationship between bifidobacteria and its host diet. Bifidobacteria, are both host- and niche-specific. Such adaptation of bifidobacterial species is considered relevant to the intestinal microecosystem and hosts’ oligosaccharides. Many species should have co-evolved with their hosts, but the phylogeny of Bifidobacterium is dissimilar to that of host animals. The discrepancy could be linked to the niche-specific evolution due to hosts’ dietary carbohydrates. The distribution of carbohydrate-active enzymes, in particular glycoside hydrolases (GHs) that metabolize unique oligosaccharides was examined. When bifidobacterial species were classified by their distribution of GH genes, five groups arose according to their hosts’ feeding behaviour. The distribution of GH genes was only weakly associated with the phylogeny of the host animals or with genomic features such as genome size. Thus, the hosts’ dietary pattern is the key determinant of the distribution and evolution of GH genes.

Methods for Biodata Analysis in different Omic Contexts

The world of Computational Biology and Bioinformatics presently integrates many different expertise, including computer science and electronic engineering. A major aim in Data Science is the development and tuning of specific computational approaches to interpret the complexity of Biology. Molecular biologists and medical doctors heavily rely on an interdisciplinary expert capable of understanding the biological background to apply algorithms for finding optimal solutions to their problems. With this problem-solving orientation, I was involved in two basic research fields: Cancer Genomics and Enzyme Proteomics. For this reason, what I developed and implemented can be considered a general effort to help data analysis both in Cancer Genomics and in Enzyme Proteomics, focusing on enzymes which catalyse all the biochemical reactions in cells. Specifically, as to Cancer Genomics I contributed to the characterization of intratumoral immune microenvironment in gastrointestinal stromal tumours (GISTs) correlating immune cell population levels with tumour subtypes. I was involved in the setup of strategies for the evaluation and standardization of different approaches for fusion transcript detection in sarcomas that can be applied in routine diagnostic. This was part of a coordinated effort of the Sarcoma working group of "Alleanza Contro il Cancro". As to Enzyme Proteomics, I generated a derived database collecting all the human proteins and enzymes which are known to be associated to genetic disease. I curated the data search in freely available databases such as PDB, UniProt, Humsavar, Clinvar and I was responsible of searching, updating, and handling the information content, and computing statistics. I also developed a web server, BENZ, which allows researchers to annotate an enzyme sequence with the corresponding Enzyme Commission number, the important feature fully describing the catalysed reaction. More to this, I greatly contributed to the characterization of the enzyme-genetic disease association, for a better classification of the metabolic genetic diseases.

S-nitrosylation homeostasis in plants: key enzymes and regulatory pathways

The nitrosylated form of glutathione (GSNO) has been acknowledged to be the most important nitrosylating agent of the plant cell, and the tuning of its intracellular concentration is of pivotal importance for photosynthetic life. During my time as a PhD student, I focused my attention on the enzymatic systems involved in the degradation of GSNO. Hence, we decided to study the structural and catalytic features of alcohol dehydrogenases (GSNOR and ADH1) from the model land plant Arabidopsis thaliana (At). These enzymes displayed a very similar 3D structure except for their active site which might explain the extreme catalytic specialization of the two enzymes. They share NAD(H) as a cofactor, but only AtGSNOR was able to catalyze the reduction of GSNO whilst being ineffective in oxidizing ethanol. Moreover, our study on the enzyme from the unicellular green alga Chlamydomonas reinhardtii (Cr) revealed how this S-nitrosoglutathione reductase (GSNOR) specifically use NADH to catalyze GSNO reduction and how its activity responds to thiol-based post-translational modifications. Contextually, the presence of NADPH-dependent GSNO-degrading systems in algal protein extract was highlighted and resulted to be relatively efficient in this model organism. This activity could be ascribed to several proteins whose contribution has not been defined yet. Intriguingly, protein extract from GSNOR null mutants of Arabidopsis displayed an increased NADPH-dependent ability to degrade GSNO and our quantitative proteome profiling on the gsnor mutant revealed the overexpression of two class 4 aldo-keto reductases (AKR), specifically AtAKR4C8 and AtAKR4C9. Later, all four class 4 AKRs showed to possess a NADPH-dependent GSNO-degrading activity. Finally, we initiated a preliminary analysis to determine the kinetic parameters of several plant proteins, including GSNOR, AKR4Cs, and thioredoxins. These data suggested GSNOR to be the most effective enzyme in catalyzing GSNO reduction because of its extremely high catalytic proficiency compared to NADPH-dependent systems.

Protein-based nanomaterials as protein heterogeneous nucleants and structural studies on enzymes from two photosynthetic organisms

Proteins, the most essential biological macromolecules, are involved in nearly every aspect of life. The elucidation of their three-dimensional structures through X-ray analysis has significantly contributed to our understanding of fundamental mechanisms in life processes. However, the obstacle of obtaining high-resolution protein crystals remains significant. Thus, searching for materials that can effectively induce nucleation of crystals is a promising and active field. This thesis work characterizes and prepares albumin nanoparticles as heterogeneous nucleants for protein crystallization. These stable Bovine Serum Albumin nanoparticles were synthesized via the desolvation method, purified efficiently, and characterized in terms of dimension, morphology, and secondary structure. The ability of BSA-NPs to induce macromolecule nucleation was tested on three model proteins, exhibiting significant results, with larger NPs inducing more nucleation. The second part of this work focuses on the structural study, mainly through X-ray crystallography, of five chloroplast and cytosolic enzymes involved in the fundamental cellular processes of two photosynthetic organisms, Chlamydomonas reinhardtii and Arabidopsis thaliana. The structures of three enzymes involved in the Calvin-Benson-Bassham Cycle, phosphoribulokinase, troseposphatisomerase, and ribulosiophosphate epimerase from Chlamydomonas reinhardtii, were solved to investigate their catalytic and regulatory mechanisms. Additionally, the structure of nitrosylated-CrTPI made it possible to identify Cys14 as a target for nitrosylation, and the crystallographic structure of CrRPE was solved for the first time, providing insights into its catalytic and regulatory properties. Finally, the structure of S-nitrosoglutathione reductase, AtGSNOR, was compared with that of AtADH1, revealing differences in their catalytic sites. Overall, seven crystallographic structures, including partially oxidized CrPRK, CrPRK/ATP, CrPRK/ADP/Ru5P, CrTPI-nitrosylated, apo-CrRPE, apo-AtGSNOR, and AtADH1-NADH, were solved and are yet to be deposited in the PDB.