Large scale analysis of protein stability in OMIM disease related human protein variants

Modern genomic techniques allow to associate several Mendelian human diseases to single residue variations in different proteins. Molecular mechanisms explaining the relationship among genotype and phenotype are still under debate. Change of protein stability upon variation appears to assume a particular relevance in annotating whether a single residue substitution can or cannot be associated to a given disease. Thermodynamic properties of human proteins and of their disease related variants are lacking. In the present work, we take advantage of the available three dimensional structure of human proteins for predicting the role of disease related variations on the perturbation of protein stability

Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions

According to databases such as OMIM, Humsavar, Clinvar and Monarch, 1494 human enzymes are presently associated to 2539 genetic diseases, 75% of which are rare (with an Orphanet code). The Mondo ontology initiative allows a standardization of the disease name into specific codes, making it possible a computational association between genes, variants, diseases, and their effects on biological processes. Here, we tackle the problem of which biological processes enzymes can affect when the protein variant is disease-associated. We adopt Reactome to describe human biological processes, and by mapping disease-associated enzymes in the Reactome pathways, we establish a Reactome-disease association. This allows a novel categorization of human monogenic and polygenic diseases based on Reactome pathways and reactions. Our analysis aims at dissecting the complexity of the human genetic disease universe, highlighting all the possible links within diseases and Reactome pathways. The novel mapping helps understanding the biochemical/molecular biology of the disease and allows a direct glimpse on the present knowledge of other molecules involved. This is useful for a complete overview of the disease molecular mechanism/s and for planning future investigations. Data are collected in DAR, a database that is free for search and available at https://dar.biocomp.unibo.it

Mutant MYO1F alters the mitochondrial network and induces tumor proliferation in thyroid cancer

Familial aggregation is a significant risk factor for the development of thyroid cancer and Familial Non-Medullary Thyroid Cancer (FNMTC) accounts for 5-7% of all NMTC. Whole Exome Sequencing analysis in the family affected by FNMTC with oncocytic features where our group previously identified a predisposing locus on chromosome 19p13.2, revealed a novel heterozygous mutation (c.400G>A, NM_012335; p.Gly134Ser) in exon 5 of MYO1F, mapping to the linkage locus. In the thyroid FRTL-5 cell model stably expressing the mutant MYO1F p.Gly134Ser protein we observed an altered mitochondrial network, with increased mitochondrial mass and a significant increase of both intracellular and extracellular Reactive Oxygen Species, compared to cells expressing the wild-type protein or carrying the empty vector. The mutation conferred a significant advantage in colony formation, invasion and anchorage independent growth. These data were corroborated by in vivo studies in zebrafish, since we demonstrated that the mutant MYO1F p.Gly134Ser, when overexpressed, can induce proliferation in whole vertebrate embryos, compared to the wild-type one. MYO1F screening in additional 192 FNMTC families identified another variant in exon 7, which leads to exon skipping, and is predicted to alter the ATP-binding domain in MYO1F. Our study identified for the first time a role for MYO1F in NMTC. This article is protected by copyright. All rights reserved

Routes of dispersion of antibiotic resistance genes from the poultry farm system

Poultry farms are hotspots for the development and spread of antibiotic resistance genes (ARGs), due to high stocking densities and extensive use of antibiotics, posing a threat of spread and contagion to workers and the external environment. Here, we applied shotgun metagenome sequencing to characterize the gut microbiome and resistome of poultry, workers and their households - also including microbiomes from the internal and external farm environment – in three different farms in Italy during a complete rearing cycle. Our results highlighted a relevant overlap among the microbiomes of poultry, workers, and their families (gut and skin), with clinically relevant ARGs and associated mobile elements shared in both poultry and human samples. On a finer scale, the reconstruction of species-level genome bins (SGBs) allowed us to delineate the dynamics of microorganism and ARGs dispersion from farm systems. We found the associations with worker microbiomes representing the main route of ARGs dispersion from poultry to human populations. Collectively, our findings clearly demonstrate the urgent need to implement more effective procedures to counteract ARGs dispersion from poultry food systems and the relevance of metagenomics-based metacommunity approaches to monitor the ARGs dispersion process for the safety of the working environment on farms

Resources and tools for rare disease variant interpretation

: Collectively, rare genetic disorders affect a substantial portion of the world's population. In most cases, those affected face difficulties in receiving a clinical diagnosis and genetic characterization. The understanding of the molecular mechanisms of these diseases and the development of therapeutic treatments for patients are also challenging. However, the application of recent advancements in genome sequencing/analysis technologies and computer-aided tools for predicting phenotype-genotype associations can bring significant benefits to this field. In this review, we highlight the most relevant online resources and computational tools for genome interpretation that can enhance the diagnosis, clinical management, and development of treatments for rare disorders. Our focus is on resources for interpreting single nucleotide variants. Additionally, we present use cases for interpreting genetic variants in clinical settings and review the limitations of these results and prediction tools. Finally, we have compiled a curated set of core resources and tools for analyzing rare disease genomes. Such resources and tools can be utilized to develop standardized protocols that will enhance the accuracy and effectiveness of rare disease diagnosis

Experimental verification of Lamb waves dispersion curves in sandwich-like structures for damage detection in single lap joints

The scientific community is looking for novel strategies to move toward sustainable and climate-neutral aviation. For fuel savings and thus for reducing the carbon footprint of an aircraft, weight reduction is recognized as one of the most effective solutions. Substituting mechanical fasteners/rivets with purely adhesive bonded joints can significantly reduce the aircraft's weight. However, ensuring the adequate reliability of purely adhesive-bonded joints requires a sound understanding of the adhesive mechanical properties and the implementation of Structural Health Monitoring (SHM) techniques. Ultrasonic Guided Waves (UGWs) are employed to investigate the structure without altering its integrity as an SHM methodology. In this framework, the description of Lamb Waves (LWs) dispersion curves allows the understanding of the material properties through the analysis of the behavior of the wave propagating in the medium. In this study experimental verification of Lamb Waves dispersion curves is conducted to evaluate the materials’ properties and the adhesively bonded joint integrity. An experimental campaign was conducted on the adherent and adhesive layers separately. The investigation narrows down the experimental methodology carried out to obtain information about the materials. The developed methodology shall compare the experimentally obtained values of the LWs group velocities at different excitation frequencies with the outcomes of the analytical model elaborated by Dr. Pant. Moreover, the signal post-processing analysis was performed to read and correctly interpret the collected data. The aim of the thesis work consisted of the development of a methodology that could fully describe the LWs dispersion curves to determine the behavior of the waves propagating in sandwich layouts. This verification process can be considered a middle step for future research in the understanding of how the wave parameters vary across the overlapping area of an adhesive joint

Studio preliminare delle prestazioni di un elicottero a rotori sincronizzati

Il progetto preso in esame in questa tesi è un elicottero a rotori sincronizzati; lo scopo è determinare le prestazioni, in termini di potenza necessaria al volo, attraverso l'elaborazione di un modello matematico implementato in ambiente Matlab, di una sua riproduzione in scala ridotta alimentata da motore elettrico. Questo particolare tipo di configurazione non ha il rotore di coda ed ha alta stabilità; tuttavia la caratteristica di avere rotori inclinati dà luogo a forze aerodinamiche di portanza aventi un'angolazione pari a quella dei rotori e ciò causa una riduzione di efficienza totale. In primo luogo, è stata esposta la teoria del disco attuatore, con le rispettive ipotesi; di seguito, l’elaborazione del modello analitico è stata svolta facendo riferimento alla teoria precedentemente descritta, applicata alla configurazione del sincrottero. Nella tesi viene analizzato l’andamento della potenza necessaria in funzione di diversi parametri sia in condizione di hovering sia in volo traslato, attraverso i necessari adattamenti della teoria del rotore singolo al caso particolare di due rotori sincronizzati. Come risultati si è ottenuto uno studio della potenza necessaria al volo espressa in funzione della velocità di avanzamento e di altri importanti parametri, mostrando comportamenti vicini alla letteratura. Riguardo gli sviluppi futuri, questa analisi è utilizzabile per il dimensionamento del motore elettrico necessario ad alimentare il modellino in scala ridotta

The biological complexity of the genotype-phenotype relation: from genes and proteins to phenotypes and diseases

To unveil the biological complexity at the basis of the genotype-phenotype relation it is fundamental to integrate knowledge that is to integrate the different omics describing the levels of biological complexity: genomics, proteomics, transcriptomics, metabolomics and interactomics. The situation gets more complicated when we move the focus to diseases and phenotypes. The identification of molecular mechanisms behind different phenotypes offers a way to understand the processes that lead to disease insurgence and progression. Another issue in computational biology is the prediction of specific phenotypic effect of gene and protein variants, to test the performance of computational methods towards experiment in vivo and in vitro. The main aim of this thesis is to study the relations among genes, variations, diseases and phenotypes with the approaches of computational biology, integrating information from different resources to make a step forward in the direction of unveiling the biological complexity. After a general introduction, we present the webservers eDGAR and PhenPath, collecting and analysing the gene-disease associations and the phenotypes-biological processes associations, respectively. We then assessed whether disease-related variations induce perturbations of the protein stability. To this aim, we developed a new predictor called INPS-3D. We test our predictors participating in international experiments on specific study cases. Thanks to the expertise acquired in the field, we also collaborate with the Sant’Orsola Genetic Medical Unit of the Department of Medicine and Surgery of the University of Bologna, building a series of models of protein structure of myosin 1F and its variants related to the thyroid cancer. Concluding, we tried to depict the biological complexity merging a large-scale approach with the analysis of specific study cases, providing webservers, tools and computation methods to help researchers in directing further experiments

Functional and Structural Features of Disease-Related Protein Variants

Modern sequencing technologies provide an unprecedented amount of data of single-nucleotide variations occurring in coding regions and leading to changes in the expressed protein sequences. A significant fraction of these single-residue variations is linked to disease onset and collected in public databases. In recent years, many scientific studies have been focusing on the dissection of salient features of disease-related variations from different perspectives. In this work, we complement previous analyses by updating a dataset of disease-related variations occurring in proteins with 3D structure. Within this dataset, we describe functional and structural features that can be of interest for characterizing disease-related variations, including major chemico-physical properties, the strength of association to disease of variation types, their effect on protein stability, their location on the protein structure, and their distribution in Pfam structural/functional protein models. Our results support previous findings obtained in different data sets and introduce Pfam models as possible fingerprints of patterns of disease related single-nucleotide variations