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Modelling infectious disease spreading is crucial for planning effective containment measures, as shown in the COVID-19 pandemic. The effectiveness of planned measures can also be measured regarding saved lives and economic resources. Therefore, introducing methods able to model the evolution and the impact of measures, as well as planning tailored and updated measures, is a crucial step. Existing models for spreading modelling belong to two main classes: (i) compartmental models based on ordinary differential equations and (ii) contact-based models based on a contact structure using an underlining layer to simulate diffusion. Nevertheless, none of these methods can leverage the high computational power of artificial intelligence and deep learning. We propose a novel framework for simulating and analysing disease progression for these methods. The framework is based on the multiscale simulation of the spreading based on using a multiscale contact model built on top of a diffusion model customised by the user. The evolution of the spreading, modelled as a graph with attributed nodes, is then mapped into a latent space through graph embedding. Finally, deep learning models are used in the latent space to analyse and forecast methods without running expensive computational simulations of the contact-based model.

COVID-19 is a viral infection, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and characterized by a complex inflammatory process and clinical immunophe-notypes. Nowadays, several alterations of immune response within the respiratory tracts as well as at the level of the peripheral blood have been well documented. Nonetheless, their effects on COVID-19-related cell heterogeneity and disease progression are less defined. Here, we performed a single-cell RNA sequencing of about 400 transcripts relevant to immune cell function including surface markers, in mononuclear cells (PBMCs) from the peripheral blood of 50 subjects, infected with SARS-CoV-2 at the diagnosis and 27 healthy blood donors as control. We found that patients with COVID-19 exhibited an increase in COVID-specific surface markers in different subsets of immune cell composition. Interestingly, the expression of cell receptors, such as IFNGR1 and CXCR4, was reduced in response to the viral infection and associated with the inhibition of the related signaling pathways and immune functions. These results highlight novel immunoreceptors, selectively expressed in COVID-19 patients, which affect the immune functionality and are correlated with clinical outcomes.

Hundreds of human proteins were found to establish transient interactions with rather degenerated consensus DNA sequences or motifs. Identifying these motifs and the genomic sites where interactions occur represent one of the most challenging research goals in modern molecular biology and bioinformatics. The last twenty years witnessed an explosion of computational tools designed to perform this task, whose performance has been last compared fifteen years ago. Here, we survey sixteen of them, benchmark their ability to identify known motifs nested in twenty-nine simulated sequence datasets, and finally report their strengths, weaknesses, and complementarity.

Mutations in genes encoding for histone methylation proteins are associated with several developmental disorders. Among them, KDM6A is the disease causative gene of type 2 Kabuki Syndrome, a rare multisystem disease. While nonsense mutations and short insertions/deletions are known to trigger pathogenic mechanisms, the functional effects of missense mutations are still uncharacterized. In this study, we demonstrate that a selected set of missense mutations significantly hamper the interaction between KDM6A and the histone H3, by modifying the dynamics of the linker domain, and then causing a loss of function effect.

The ultrafast structural dynamics of water following inner-shell ionization is a crucial issue in high-energy radiation chemistry. We have exposed isolated water molecules to a short x-ray pulse from a free-electron laser and detected momenta of all produced ions in coincidence. By combining experimental results and theoretical modeling, we can image dissociation dynamics of individual molecules in unprecedented detail. We reveal significant molecular structural dynamics in H2O2+, such as asymmetric deformation and bond-angle opening, leading to two-body or three-body fragmentation on a timescale of a few femtoseconds. We thus reconstruct several snapshots of structural dynamics at different time intervals, which highlight dynamical patterns that are relevant as initiating steps of subsequent radiation-damage processes.

Hepatocellular carcinoma (HCC) is a leading cause of cancer‐related death worldwide. A foremost risk factor for HCC is obesity/metabolic syndrome‐related non‐alcoholic fatty liver disease (NAFLD) and non‐alcoholic steatohepatitis (NASH), which is prompted by remarkable changes in transcription patterns of genes enriching metabolic, immune/inflammatory, and circadian pathways. Epigenetic mechanisms play a role in NAFLD‐associated HCC, and macroH2A1, a variant of histone H2A, is involved in the pathogenesis modulating the expression of oncogenes and/or tumor suppressor genes and interacting with SIRT1, which crucially impacts the circadian clock circuitry. Hence, we aimed to appraise if and how macroH2A1 regulated the expression patterns of circadian genes in the setting of NAFLD‐associated HCC. We took advantage of an in vitro model of liver cancer represented by HepG2 (human hepatocarcinoma) cells stably knocked down for macroH2A1 and conducted whole transcriptome profiling and deep phenotyping analysis. We found up‐regulation of PER1 along with several deregulated circadian genes, enriching several important pathways and functions related to cancer onset and progression, such as epithelial‐to‐mesenchymal transition, cell cycle deregulation, and DNA damage. PER1 silencing partially mitigated the malignant phenotype induced by the loss of macroH2A1 in HCC cells. In conclusion, our findings suggest a modulatory role for the core circadian protein PER1 in liver carcinogenesis in the context of a lack of the macroH2A1 epigenetic and transcriptional landscape.

Numerous lines of evidence have shown that the interaction between the nuclear and mitochondrial genomes ensures the efficient functioning of the OXPHOS complexes, with substantial implications in bioenergetics, adaptation, and disease. Their interaction is a fascinating and complex trait of the eukaryotic cell that MitImpact explores with its third major release. MitImpact expands its collection of genomic, clinical, and functional annotations of all non-synonymous substitutions of the human mitochondrial genome with new information on putative Compensated Pathogenic Deviations and co-varying amino acid sites of the Respiratory Chain subunits. It further provides evidence of energetic and structural residue compensation by techniques of molecular dynamics simulation. MitImpact is freely accessible at http://mitimpact.css-mendel.it.

Lysine-specific methyltransferase 2A (KMT2A) is responsible for methylation of histone H3 (K4H3me) and contributes to chromatin remodeling, acting as “writer” of the epigenetic machinery. Mutations in KMT2A were first reported in Wiedemann–Steiner syndrome (WDSTS). More recently, KMT2A variants have been described in probands with a specific clinical diagnosis comprised in the so-called chromatinopathies. Such conditions, including WDSTS, are a group of overlapping disorders caused by mutations in genes coding for the epigenetic machinery. Among them, Rubinstein–Taybi syndrome (RSTS) is mainly caused by heterozygous pathogenic variants in CREBBP or EP300. In this work, we used next generation sequencing (either by custom-made panel or by whole exome) to identify alternative causative genes in individuals with a RSTS-like phenotype negative to CREBBP and EP300 mutational screening. In six patients we identified different novel unreported variants in KMT2A gene. The identified variants are de novo in at least four out of six tested individuals and all of them display some typical RSTS phenotypic features but also WDSTS specific signs. This study reinforces the concept that germline variants affecting the epigenetic machinery lead to a shared molecular effect (alteration of the chromatin state) determining superimposable clinical conditions.