The explosion of the data both in the biomedical research and in the healthcare systems demands urgent solutions. In particular, the research in omics sciences is moving from a hypothesis-driven to a data-driven approach. Healthcare is additionally always asking for a tighter integration with biomedical data in order to promote personalized medicine and to provide better treatments. Efficient analysis and interpretation of Big Data opens new avenues to explore molecular biology, new questions to ask about physiological and pathological states, and new ways to answer these open issues. Such analyses lead to better understanding of diseases and development of better and personalized diagnostics and therapeutics. However, such progresses are directly related to the availability of new solutions to deal with this huge amount of information. New paradigms are needed to store and access data, for its annotation and integration and finally for inferring knowledge and making it available to researchers. Bioinformatics can be viewed as the “glue” for all these processes. A clear awareness of present high performance computing (HPC) solutions in bioinformatics, Big Data analysis paradigms for computational biology, and the issues that are still open in the biomedical and healthcare fields represent the starting point to win this challenge.

Recombination signal sequences (RSSs) flanking V, D and J gene segments are recognized and cut by the VDJ recombinase during development of B and T lymphocytes. All RSSs are composed of seven conserved nucleotides, followed by a spacer (containing either 12 � 1 or 23 � 1 poorly conserved nucleotides) and a conserved nonamer. Errors in V(D)J recombination, including cleavage of cryptic RSS outside the immunoglobulin and T cell receptor loci, are associated with oncogenic translocations observed in some lymphoid malignancies. We present in this paper the RSSsite web server, which is available from the address http://www.itb.cnr.it/rss. RSSsite consists of a web-accessible database, RSSdb, for the identification of pre-computed potential RSSs, and of the related search tool, DnaGrab, which allows the scoring of potential RSSs in user-supplied sequences. This latter algorithm makes use of probability models, which can be recasted to Bayesian network, taking into account correlations between groups of positions of a sequence, developed starting from specific reference sets of RSSs. In validation laboratory experiments, we selected 33 predicted cryptic RSSs (cRSSs) from 11 chromosomal regions outside the immunoglobulin and TCR loci for functional testing.

Workflows are among the most commonly used tools in a variety of execution environments. Many of them target a specific environment; few of them make it possible to execute an entire workflow in different environments, e.g. Kubernetes and batch clusters. We present a novel approach to workflow execution, called StreamFlow, that complements the workflow graph with the declarative description of potentially complex execution environments, and that makes it possible the execution onto multiple sites not sharing a common data space. StreamFlow is then exemplified on a novel bioinformatics pipeline for single cell transcriptomic data analysis workflow.

Breast cancer is one of the most common cancer types. Due to the complexity of this disease, it is important to face its study with an integrated and multilevel approach, from genes, transcripts and proteins to molecular networks, cell populations and tissues. According to the systems biology perspective, the biological functions arise from complex networks: in this context, concepts like molecular pathways, protein-protein interactions (PPIs), mathematical models and ontologies play an important role for dissecting such complexity.

Aberrant induction of type I IFN is a hallmark of the inherited encephalopathy Aicardi-Goutières syndrome (AGS), but the mechanisms triggering disease in the human central nervous system (CNS) remain elusive. Here, we generated human models of AGS using genetically modified and patient-derived pluripotent stem cells harboring TREX1 or RNASEH2B loss-of-function alleles. Genome-wide transcriptomic analysis reveals that spontaneous proinflammatory activation in AGS astrocytes initiates signaling cascades impacting multiple CNS cell subsets analyzed at the single-cell level. We identify accumulating DNA damage, with elevated R-loop and micronuclei formation, as a driver of STING- and NLRP3-related inflammatory responses leading to the secretion of neurotoxic mediators. Importantly, pharmacological inhibition of proapoptotic or inflammatory cascades in AGS astrocytes prevents neurotoxicity without apparent impact on their increased type I IFN responses. Together, our work identifies DNA damage as a major driver of neurotoxic inflammation in AGS astrocytes, suggests a role for AGS gene products in R-loop homeostasis, and identifies common denominators of disease that can be targeted to prevent astrocyte-mediated neurotoxicity in AGS.

Glioblastoma multiforme (GBM) is the most common and lethal brain tumor characterized by a strongly immunosuppressive tumor microenvironment (TME) that represents a barrier also for the development of effective immunotherapies. The possibility to revert this hostile TME by immunoactivating cytokines is hampered by the severe toxicity associated with their systemic administration. Here, we exploited a lentiviral vector–based platform to engineer hematopoietic stem cells ex vivo with the aim of releasing, via their tumor-infiltrating monocyte/macrophage progeny, interferon-α (IFN-α) or interleukin-12 (IL-12) at the tumor site with spatial and temporal selectivity. Taking advantage of a syngeneic GBM mouse model, we showed that inducible release of IFN-α within the TME achieved robust tumor inhibition up to eradication and outperformed systemic treatment with the recombinant protein in terms of efficacy, tolerability, and specificity. Single-cell RNA sequencing of the tumor immune infiltrate revealed reprogramming of the immune microenvironment toward a proinflammatory and antitumoral state associated with loss of a macrophage subpopulation shown to be associated with poor prognosis in human GBM. The spatial and temporal control of IL-12 release was critical to overcome an otherwise lethal hematopoietic toxicity while allowing to fully exploit its antitumor activity. Overall, our findings demonstrate a potential therapeutic approach for GBM and set the bases for a recently launched first-in-human clinical trial in patients with GBM.