Functional and Taxonomic Traits of the Gut Microbiota in Type 1 Diabetes Children at the Onset: A Metaproteomic Study

Type 1 diabetes (T1D) is a chronic autoimmune metabolic disorder with onset in pediatric/adolescent age, characterized by insufficient insulin production, due to a progressive destruction of pancreatic beta-cells. Evidence on the correlation between the human gut microbiota (GM) composition and T1D insurgence has been recently reported. In particular, 16S rRNA-based metagenomics has been intensively employed in the last decade in a number of investigations focused on GM representation in relation to a pre-disease state or to a response to clinical treatments. On the other hand, few works have been published using alternative functional omics, which is more suitable to provide a different interpretation of such a relationship. In this work, we pursued a comprehensive metaproteomic investigation on T1D children compared with a group of siblings (SIBL) and a reference control group (CTRL) composed of aged matched healthy subjects, with the aim of finding features in the T1D patients' GM to be related with the onset of the disease. Modulated metaproteins were found either by comparing T1D with CTRL and SIBL or by stratifying T1D by insulin need (IN), as a proxy of beta-cells damage, showing some functional and taxonomic traits of the GM, possibly related to the disease onset at different stages of severity

Shifts of Faecal Microbiota during Sporadic Colorectal Carcinogenesis

Gut microbiota has been implicated in the etiopathogenesis of colorectal cancer. The development of colorectal cancer is a multistep process by which healthy epithelium slowly develops into preneoplastic lesions, which in turn progress into malignant carcinomas over time. In particular, sporadic colorectal cancers can arise from adenomas (about 85% of cases) or serrated polyps through the "adenoma-carcinoma" or the "serrated polyp-carcinoma" sequences, respectively. In this study, we performed 16 S rRNA gene sequencing of bacterial DNA extracted from faecal samples to compare the microbiota of healthy subjects and patients with different preneoplastic and neoplastic lesions. We identified putative microbial biomarkers associated with stage-specific progression of colorectal cancer. In particular, bacteria belonging to the Firmicutes and Actinobacteria phyla, as well as members of the Lachnospiraceae family, proved to be specific of the faecal microbiota of patients with preneoplastic lesions, including adenomas and hyperplastic polyps. On the other hand, two families of the Proteobacteria phylum, Alcaligeneaceae and Enterobacteriaceae, with Sutterella and Escherichia/Shigella being the most representative genera, appeared to be associated with malignancy. These findings, once confirmed on larger cohorts of patients, can represent an important step towards the development of more effective diagnostic strategies

Gut Microbiota Functional Traits, Blood pH, and Anti-GAD Antibodies Concur in the Clinical Characterization of T1D at Onset

Alterations of gut microbiota have been identified before clinical manifestation of type 1 diabetes (T1D). To identify the associations amongst gut microbiome profile, metabolism and disease markers, the 16S rRNA-based microbiota profiling and H-1-NMR metabolomic analysis were performed on stool samples of 52 T1D patients at onset, 17 T1D siblings and 57 healthy subjects (CTRL). Univariate, multivariate analyses and classification models were applied to clinical and -omic integrated datasets. In T1D patients and their siblings, Clostridiales and Dorea were increased and Dialister and Akkermansia were decreased compared to CTRL, while in T1D, Lachnospiraceae were higher and Collinsella was lower, compared to siblings and CTRL. Higher levels of isobutyrate, malonate, Clostridium, Enterobacteriaceae, Clostridiales, Bacteroidales, were associated to T1D compared to CTRL. Patients with higher anti-GAD levels showed low abundances of Roseburia, Faecalibacterium and Alistipes and those with normal blood pH and low serum HbA(1c) levels showed high levels of purine and pyrimidine intermediates. We detected specific gut microbiota profiles linked to both T1D at the onset and to diabetes familiarity. The presence of specific microbial and metabolic profiles in gut linked to anti-GAD levels and to blood acidosis can be considered as predictive biomarker associated progression and severity of T1D

Gut microbiota functional profiling in autism spectrum disorders: bacterial VOCs and related metabolic pathways acting as disease biomarkers and predictors

BackgroundAutism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder. Major interplays between the gastrointestinal (GI) tract and the central nervous system (CNS) seem to be driven by gut microbiota (GM). Herein, we provide a GM functional characterization, based on GM metabolomics, mapping of bacterial biochemical pathways, and anamnestic, clinical, and nutritional patient metadata.MethodsFecal samples collected from children with ASD and neurotypical children were analyzed by gas-chromatography mass spectrometry coupled with solid phase microextraction (GC–MS/SPME) to determine volatile organic compounds (VOCs) associated with the metataxonomic approach by 16S rRNA gene sequencing. Multivariate and univariate statistical analyses assessed differential VOC profiles and relationships with ASD anamnestic and clinical features for biomarker discovery. Multiple web-based and machine learning (ML) models identified metabolic predictors of disease and network analyses correlated GM ecological and metabolic patterns.ResultsThe GM core volatilome for all ASD patients was characterized by a high concentration of 1-pentanol, 1-butanol, phenyl ethyl alcohol; benzeneacetaldehyde, octadecanal, tetradecanal; methyl isobutyl ketone, 2-hexanone, acetone; acetic, propanoic, 3-methyl-butanoic and 2-methyl-propanoic acids; indole and skatole; and o-cymene. Patients were stratified based on age, GI symptoms, and ASD severity symptoms. Disease risk prediction allowed us to associate butanoic acid with subjects older than 5 years, indole with the absence of GI symptoms and low disease severity, propanoic acid with the ASD risk group, and p-cymene with ASD symptoms, all based on the predictive CBCL-EXT scale. The HistGradientBoostingClassifier model classified ASD patients vs. CTRLs by an accuracy of 89%, based on methyl isobutyl ketone, benzeneacetaldehyde, phenyl ethyl alcohol, ethanol, butanoic acid, octadecane, acetic acid, skatole, and tetradecanal features. LogisticRegression models corroborated methyl isobutyl ketone, benzeneacetaldehyde, phenyl ethyl alcohol, skatole, and acetic acid as ASD predictors.ConclusionOur results will aid the development of advanced clinical decision support systems (CDSSs), assisted by ML models, for advanced ASD-personalized medicine, based on omics data integrated into electronic health/medical records. Furthermore, new ASD screening strategies based on GM-related predictors could be used to improve ASD risk assessment by uncovering novel ASD onset and risk predictors

AML1/ETO Oncoprotein Is Directed to AML1 Binding Regions and Co-Localizes with AML1 and HEB on Its Targets

A reciprocal translocation involving chromosomes 8 and 21 generates the AML1/ETO oncogenic transcription factor that initiates acute myeloid leukemia by recruiting co-repressor complexes to DNA. AML1/ETO interferes with the function of its wild-type counterpart, AML1, by directly targeting AML1 binding sites. However, transcriptional regulation determined by AML1/ETO probably relies on a more complex network, since the fusion protein has been shown to interact with a number of other transcription factors, in particular E-proteins, and may therefore target other sites on DNA. Genome-wide chromatin immunoprecipitation and expression profiling were exploited to identify AML1/ETO-dependent transcriptional regulation. AML1/ETO was found to co-localize with AML1, demonstrating that the fusion protein follows the binding pattern of the wild-type protein but does not function primarily by displacing it. The DNA binding profile of the E-protein HEB was grossly rearranged upon expression of AML1/ETO, and the fusion protein was found to co-localize with both AML1 and HEB on many of its regulated targets. Furthermore, the level of HEB protein was increased in both primary cells and cell lines expressing AML1/ETO. Our results suggest a major role for the functional interaction of AML1/ETO with AML1 and HEB in transcriptional regulation determined by the fusion protein

Early diagnosis, disease stage and prognosis in wild‐type transthyretin amyloid cardiomyopathy: The DIAMOND study

Aims: Disease staging and prognostic scoring in wild-type transthyretin-related cardiac amyloidosis (ATTRwt-CA) can be captured by two systems (NAC and Columbia scores). However, uncertainty remains as epidemiology of the disease is evolving rapidly. We evaluated features associated with staging systems across ATTRwt-CA patients from different diagnostic pathways, and their association with prognosis. Methods: We performed an analysis on DIAMOND patients with available data to evaluate NAC and Columbia score. DIAMOND was a retrospective study from 17 Italian referral centres for CA, enrolling 1281 patients diagnosed between 2016 and 2021, and aimed at describing characteristics of pathways leading to ATTRwt-CA diagnosis. Of the original cohort, 811 patients were included in this analysis. Each patient had NAC and Columbia score calculated. Patients were grouped according to NAC and Columbia scoring classes. We described characteristics of patients according to staging classes and diagnostic pathways at diagnosis. Prevalence of early diagnoses, defined as NAC Ia, NYHA class I, no use of diuretics, no history of heart failure (HF) hospitalizations nor of atrial fibrillation prior to diagnosis, was investigated. Finally, prognostic variables were tested alone and grouped as NAC or Columbia scores in Cox univariate and multivariate regression analyses. Prognosis was investigated as all-cause mortality, in the whole population and dividing patients in HF versus other diagnostic pathways. Results: Only 1% of the study population had an early ATTRwt-CA diagnosis. Distribution of prognostic variables and of NAC and Columbia classes was heterogeneous across diagnostic pathways. The prevalence of NAC III and Columbia III was higher in the HF diagnostic pathway, but all NAC and Columbia classes were present in all pathways. Both NAC and Columbia scores were associated with all-cause mortality at univariate Cox regression analysis in the whole population, in patients from the HF diagnostic pathway and in those from other pathways. At multivariate analysis, Columbia score remained significantly associated with the outcome, together with age at diagnosis, left ventricular ejection fraction and maximal wall thickness. Conclusions: In this contemporary nationwide cohort, an ATTRwt-CA early diagnosis was very rare. Disease staging with NAC and Columbia scoring systems determined classes of patients with heterogeneous features. Both scores were significantly associated with mortality, but other variables also had prognostic significance

Clinical Features, Cardiovascular Risk Profile, and Therapeutic Trajectories of Patients with Type 2 Diabetes Candidate for Oral Semaglutide Therapy in the Italian Specialist Care

Introduction: This study aimed to address therapeutic inertia in the management of type 2 diabetes (T2D) by investigating the potential of early treatment with oral semaglutide. Methods: A cross-sectional survey was conducted between October 2021 and April 2022 among specialists treating individuals with T2D. A scientific committee designed a data collection form covering demographics, cardiovascular risk, glucose control metrics, ongoing therapies, and physician judgments on treatment appropriateness. Participants completed anonymous patient questionnaires reflecting routine clinical encounters. The preferred therapeutic regimen for each patient was also identified. Results: The analysis was conducted on 4449 patients initiating oral semaglutide. The population had a relatively short disease duration (42%  60% of patients, and more often than sitagliptin or empagliflozin. Conclusion: The study supports the potential of early implementation of oral semaglutide as a strategy to overcome therapeutic inertia and enhance T2D management

STRUCTURAL BIOINFORMATICS: A WINDOW TO OBSERVE THE PROTEIN UNIVERSE

Analyzing huge amounts of data that are stored in biologically relevant databases to find information to be translated into new general knowledge, is the essence of Bioinformatics. During my PhD training, have implemented Structural Bioinformatics procedures to derive information from the wealth of structural data that is publically available from the Protein Data Bank. From the thousands of experimentally derived structures where proteins are bound to other proteins, nucleic acids or small organic molecules, We found signals for interpreting the rationale underneath Nature’s assignment of codon multiplicity. The fact that arginine appeared as the most common amino acid at protein-nucleic acid interfaces, not only explained the reason why the latter amino acids has six different codons, in spite of its average occurrence in proteins [Gardini S, Cheli S, Baroni S, Di Lascio G, Mangiavacchi G, Micheletti N, Monaco CL, Savini L, Alocci D, Mangani S, Niccolai N. On Nature's Strategy for Assigning Genetic Code Multiplicity. PLoS One. 2016 Feb 5;11(2):e0148174], but also suggested possible roles of natural amino acids to determine specific dynamics of protein-protein and protein-nucleic acid interactions. I investigated in details the dynamics of protein-DNA approaches, by analysing amino acid occurrence at protein-DNA interfaces in a series of refined PDB files. The presence of negatively charged side chains of aspartate and glutamate at the protein-DNA interface was observed in a large majority of DNA complexes with enzymes such as polymerases, helicases, topoisomerases etc., that is in all those structures related to systems requiring a very dynamic intermolecular approach. Whenever a more static protein-DNA is needed, for instance in the case of histons, the largest presence of interfacial arginines is found to ensure sticky interactions between its guanidine side chains with DNA phosphate backbone groups. Transcription factors, interestingly, exhibited an intermediate behaviour [Gardini S, Furini S, Santucci A, Niccolai N. A structural bioinformatics investigation on protein-DNA complexes delineates their modes of interaction. Mol Biosyst. 2017 May 2;13(5):1010-1017]. The latter results, having an extreme relevance in possible biotechnological applications, stimulated Gardini to test, with computational and experimental procedures, the validity of his hypothesis. This activity has been carried out in Prof. Matteo Dal Peraro’s lab in Losanna and in Prof. Annalisa Pastore’s lab in London. He tried to use Molecular Dynamics simulations by using the computational facilities of the Swiss lab to confirm how Arg/Lys replacements could modulate protein sliding along DNA rails. In London, he tried to engineer amino acid mutations on model systems of DNA related enzymes. Both investigations will require additional time, as in the three months spent both in Switzerland and United Kingdom, he could not achieve unambiguous results. A third Structural Bioinformatics project is now close to its completion that is to find messages in protein core compositions, which can determine specific protein folding. In this respect, encouraging results have been obtained and a manuscript is in preparation

A structural bioinformatics investigation on protein–DNA complexes delineates their modes of interaction

A non-redundant dataset of 629 protein–DNA complexes has been used to investigate on amino acid composition of protein-DNA interfaces. Structural proteins, transcription factors and DNA-related enzymes show specific patterns accounting for different modes of their interaction with DNA.</p