Modulating the immune response to SARS-CoV-2 by different nanocarriers delivering an mRNA expressing trimeric RBD of the spike protein: COVARNA Consortium.

Vaccines based on mRNA technology have revolutionized the field. In fact, lipid nanoparticles (LNP) formulated with mRNA are the preferential vaccine platform used in the fight against SARS-CoV-2 infection, with wider application against other diseases. The high demand and property right protection of the most potent cationic/ionizable lipids used for LNP formulation of COVID-19 mRNA vaccines have promoted the design of alternative nanocarriers for nucleic acid delivery. In this study we have evaluated the immunogenicity and efficacy of different rationally designed lipid and polymeric-based nanoparticle prototypes against SARS-CoV-2 infection. An mRNA coding for a trimeric soluble form of the receptor binding domain (RBD) of the spike (S) protein from SARS-CoV-2 was encapsulated using different components to form nanoemulsions (NE), nanocapsules (NC) and lipid nanoparticles (LNP). The toxicity and biological activity of these prototypes were evaluated in cultured cells after transfection and in mice following homologous prime/boost immunization. Our findings reveal good levels of RBD protein expression with most of the formulations. In C57BL/6 mice immunized intramuscularly with two doses of formulated RBD-mRNA, the modified lipid nanoparticle (mLNP) and the classical lipid nanoparticle (LNP-1) were the most effective delivery nanocarriers at inducing binding and neutralizing antibodies against SARS-CoV-2. Both prototypes fully protected susceptible K18-hACE2 transgenic mice from morbidity and mortality following a SARS-CoV-2 challenge. These results highlight that modulation of mRNAs immunogenicity can be achieved by using alternative nanocarriers and support further assessment of mLNP and LNP-1 prototypes as delivery vehicles for mRNA vaccines.

DEBBIE: The Open Access Database of Experimental Scaffolds and Biomaterials Built Using an Automated Text Mining Pipeline.

Biomaterials research output has experienced an exponential increase over the last three decades. The majority of research is published in the form of scientific articles and is therefore available as unstructured text, making it a challenging input for computational processing. Computational tools are becoming essential to overcome this information overload. Among them, text mining systems present an attractive option for the automated extraction of information from text documents into structured datasets. This work presents the first automated system for biomaterial related information extraction from the National Library of Medicine's premier bibliographic database (MEDLINE) research abstracts into a searchable database. The system is a text mining pipeline that periodically retrieves abstracts from PubMed and identifies research and clinical studies of biomaterials. Thereafter, the pipeline identifies sixteen concept types of interest in the abstract using the Biomaterials Annotator, a tool for biomaterials Named Entity Recognition (NER). These concepts of interest, along with the abstract and relevant metadata are then deposited in DEBBIE, the Database of Experimental Biomaterials and their Biological Effect. DEBBIE is accessible through a web application that provides keyword searches and displays results in an intuitive and meaningful manner, aiming to facilitate an efficient mapping and organization of biomaterials information.

Identifying causative mechanisms linking early-life stress to psycho-cardio-metabolic multi-morbidity: The EarlyCause project.

INTRODUCTION: Depression, cardiovascular diseases and diabetes are among the major non-communicable diseases, leading to significant disability and mortality worldwide. These diseases may share environmental and genetic determinants associated with multimorbid patterns. Stressful early-life events are among the primary factors associated with the development of mental and physical diseases. However, possible causative mechanisms linking early life stress (ELS) with psycho-cardio-metabolic (PCM) multi-morbidity are not well understood. This prevents a full understanding of causal pathways towards the shared risk of these diseases and the development of coordinated preventive and therapeutic interventions. METHODS AND ANALYSIS: This paper describes the study protocol for EarlyCause, a large-scale and inter-disciplinary research project funded by the European Union's Horizon 2020 research and innovation programme. The project takes advantage of human longitudinal birth cohort data, animal studies and cellular models to test the hypothesis of shared mechanisms and molecular pathways by which ELS shapes an individual's physical and mental health in adulthood. The study will research in detail how ELS converts into biological signals embedded simultaneously or sequentially in the brain, the cardiovascular and metabolic systems. The research will mainly focus on four biological processes including possible alterations of the epigenome, neuroendocrine system, inflammatome, and the gut microbiome. Life-course models will integrate the role of modifying factors as sex, socioeconomics, and lifestyle with the goal to better identify groups at risk as well as inform promising strategies to reverse the possible mechanisms and/or reduce the impact of ELS on multi-morbidity development in high-risk individuals. These strategies will help better manage the impact of multi-morbidity on human health and the associated risk.

An agenda-setting paper on data sharing platforms: euCanSHare workshop.

Various data sharing platforms are being developed to enhance the sharing of cohort data by addressing the fragmented state of data storage and access systems. However, policy challenges in several domains remain unresolved. The euCanSHare workshop was organized to identify and discuss these challenges and to set the future research agenda. Concerns over the multiplicity and long-term sustainability of platforms, lack of resources, access of commercial parties to medical data, credit and recognition mechanisms in academia and the organization of data access committees are outlined. Within these areas, solutions need to be devised to ensure an optimal functioning of platforms.

Mutations in JMJD1C are involved in Rett syndrome and intellectual disability.

PURPOSE: Autism spectrum disorders are associated with defects in social response and communication that often occur in the context of intellectual disability. Rett syndrome is one example in which epilepsy, motor impairment, and motor disturbance may co-occur. Mutations in histone demethylases are known to occur in several of these syndromes. Herein, we aimed to identify whether mutations in the candidate histone demethylase JMJD1C (jumonji domain containing 1C) are implicated in these disorders. METHODS: We performed the mutational and functional analysis of JMJD1C in 215 cases of autism spectrum disorders, intellectual disability, and Rett syndrome without a known genetic defect. RESULTS: We found seven JMJD1C variants that were not present in any control sample (~ 6,000) and caused an amino acid change involving a different functional group. From these, two de novo JMJD1C germline mutations were identified in a case of Rett syndrome and in a patient with intellectual disability. The functional study of the JMJD1C mutant Rett syndrome patient demonstrated that the altered protein had abnormal subcellular localization, diminished activity to demethylate the DNA damage-response protein MDC1, and reduced binding to MECP2. We confirmed that JMJD1C protein is widely expressed in brain regions and that its depletion compromises dendritic activity. CONCLUSIONS: Our findings indicate that mutations in JMJD1C contribute to the development of Rett syndrome and intellectual disability.Genet Med 18 1, 378-385.

Molecular dynamics simulations: advances and applications.

Molecular dynamics simulations have evolved into a mature technique that can be used effectively to understand macromolecular structure-to-function relationships. Present simulation times are close to biologically relevant ones. Information gathered about the dynamic properties of macromolecules is rich enough to shift the usual paradigm of structural bioinformatics from studying single structures to analyze conformational ensembles. Here, we describe the foundations of molecular dynamics and the improvements made in the direction of getting such ensemble. Specific application of the technique to three main issues (allosteric regulation, docking, and structure refinement) is discussed.

Non-coding recurrent mutations in chronic lymphocytic leukaemia.

Chronic lymphocytic leukaemia (CLL) is a frequent disease in which the genetic alterations determining the clinicobiological behaviour are not fully understood. Here we describe a comprehensive evaluation of the genomic landscape of 452 CLL cases and 54 patients with monoclonal B-lymphocytosis, a precursor disorder. We extend the number of CLL driver alterations, including changes in ZNF292, ZMYM3, ARID1A and PTPN11. We also identify novel recurrent mutations in non-coding regions, including the 3' region of NOTCH1, which cause aberrant splicing events, increase NOTCH1 activity and result in a more aggressive disease. In addition, mutations in an enhancer located on chromosome 9p13 result in reduced expression of the B-cell-specific transcription factor PAX5. The accumulative number of driver alterations (0 to ≥4) discriminated between patients with differences in clinical behaviour. This study provides an integrated portrait of the CLL genomic landscape, identifies new recurrent driver mutations of the disease, and suggests clinical interventions that may improve the management of this neoplasia.

Comprehensive characterization of complex structural variations in cancer by directly comparing genome sequence reads.

The development of high-throughput sequencing technologies has advanced our understanding of cancer. However, characterizing somatic structural variants in tumor genomes is still challenging because current strategies depend on the initial alignment of reads to a reference genome. Here, we describe SMUFIN (somatic mutation finder), a single program that directly compares sequence reads from normal and tumor genomes to accurately identify and characterize a range of somatic sequence variation, from single-nucleotide variants (SNV) to large structural variants at base pair resolution. Performance tests on modeled tumor genomes showed average sensitivity of 92% and 74% for SNVs and structural variants, with specificities of 95% and 91%, respectively. Analyses of aggressive forms of solid and hematological tumors revealed that SMUFIN identifies breakpoints associated with chromothripsis and chromoplexy with high specificity. SMUFIN provides an integrated solution for the accurate, fast and comprehensive characterization of somatic sequence variation in cancer.

A genome-wide association study identifies a novel locus at 6q22.1 associated with ulcerative colitis.

The genetic analysis of ulcerative colitis (UC) has provided new insights into the etiology of this prevalent inflammatory bowel disease. However, most of the heritability of UC (>70%) has still not been characterized. To identify new risk loci for UC we have performed the first genome-wide association study (GWAS) in a Southern European population and undertaken a meta-analysis study combining the newly genotyped 825 UC patients and 1525 healthy controls from Spain with the six previously published GWAS comprising 6687 cases and 19 718 controls from Northern-European ancestry. We identified a novel locus with genome-wide significance at 6q22.1 [rs2858829, P = 8.97 × 10(-9), odds ratio (OR) (95% confidence interval, CI] = 1.12 (1.08-1.16)] that was validated with genotype data from a replication cohort of the same Southern European ancestry consisting in 1073 cases and 1279 controls [combined P = 7.59 × 10(-10), OR (95% CI) = 1.12 (1.08-1.16)]. Furthermore, we confirmed the association of 33 reported associations with UC and we nominally validated the GWAS results of nine new risk loci (P < 0.05, same direction of effect). SNP rs2858829 lies in an intergenic region and is a strong cis-eQTL for FAM26F gene, a gene that is shown to be selectively upregulated in UC colonic mucosa with active inflammation. Our results provide new insight into the genetic risk background of UC, confirming that there is a genetic risk component that differentiates from Crohn's Disease, the other major form of inflammatory bowel disease.

Epigenomic analysis detects widespread gene-body DNA hypomethylation in chronic lymphocytic leukemia.

We have extensively characterized the DNA methylomes of 139 patients with chronic lymphocytic leukemia (CLL) with mutated or unmutated IGHV and of several mature B-cell subpopulations through the use of whole-genome bisulfite sequencing and high-density microarrays. The two molecular subtypes of CLL have differing DNA methylomes that seem to represent epigenetic imprints from distinct normal B-cell subpopulations. DNA hypomethylation in the gene body, targeting mostly enhancer sites, was the most frequent difference between naive and memory B cells and between the two molecular subtypes of CLL and normal B cells. Although DNA methylation and gene expression were poorly correlated, we identified gene-body CpG dinucleotides whose methylation was positively or negatively associated with expression. We have also recognized a DNA methylation signature that distinguishes new clinico-biological subtypes of CLL. We propose an epigenomic scenario in which differential methylation in the gene body may have functional and clinical implications in leukemogenesis.

Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia.

Here we perform whole-exome sequencing of samples from 105 individuals with chronic lymphocytic leukemia (CLL), the most frequent leukemia in adults in Western countries. We found 1,246 somatic mutations potentially affecting gene function and identified 78 genes with predicted functional alterations in more than one tumor sample. Among these genes, SF3B1, encoding a subunit of the spliceosomal U2 small nuclear ribonucleoprotein (snRNP), is somatically mutated in 9.7% of affected individuals. Further analysis in 279 individuals with CLL showed that SF3B1 mutations were associated with faster disease progression and poor overall survival. This work provides the first comprehensive catalog of somatic mutations in CLL with relevant clinical correlates and defines a large set of new genes that may drive the development of this common form of leukemia. The results reinforce the idea that targeting several well-known genetic pathways, including mRNA splicing, could be useful in the treatment of CLL and other malignancies.

Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia.

Chronic lymphocytic leukaemia (CLL), the most frequent leukaemia in adults in Western countries, is a heterogeneous disease with variable clinical presentation and evolution. Two major molecular subtypes can be distinguished, characterized respectively by a high or low number of somatic hypermutations in the variable region of immunoglobulin genes. The molecular changes leading to the pathogenesis of the disease are still poorly understood. Here we performed whole-genome sequencing of four cases of CLL and identified 46 somatic mutations that potentially affect gene function. Further analysis of these mutations in 363 patients with CLL identified four genes that are recurrently mutated: notch 1 (NOTCH1), exportin 1 (XPO1), myeloid differentiation primary response gene 88 (MYD88) and kelch-like 6 (KLHL6). Mutations in MYD88 and KLHL6 are predominant in cases of CLL with mutated immunoglobulin genes, whereas NOTCH1 and XPO1 mutations are mainly detected in patients with unmutated immunoglobulins. The patterns of somatic mutation, supported by functional and clinical analyses, strongly indicate that the recurrent NOTCH1, MYD88 and XPO1 mutations are oncogenic changes that contribute to the clinical evolution of the disease. To our knowledge, this is the first comprehensive analysis of CLL combining whole-genome sequencing with clinical characteristics and clinical outcomes. It highlights the usefulness of this approach for the identification of clinically relevant mutations in cancer.