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.

The Quest for Orthologs orthology benchmark service in 2022.

The Orthology Benchmark Service (https://orthology.benchmarkservice.org) is the gold standard for orthology inference evaluation, supported and maintained by the Quest for Orthologs consortium. It is an essential resource to compare existing and new methods of orthology inference (the bedrock for many comparative genomics and phylogenetic analysis) over a standard dataset and through common procedures. The Quest for Orthologs Consortium is dedicated to maintaining the resource up to date, through regular updates of the Reference Proteomes and increasingly accessible data through the OpenEBench platform. For this update, we have added a new benchmark based on curated orthology assertion from the Vertebrate Gene Nomenclature Committee, and provided an example meta-analysis of the public predictions present on the platform.

The Quest for Orthologs benchmark service and consensus calls in 2020.

The identification of orthologs-genes in different species which descended from the same gene in their last common ancestor-is a prerequisite for many analyses in comparative genomics and molecular evolution. Numerous algorithms and resources have been conceived to address this problem, but benchmarking and interpreting them is fraught with difficulties (need to compare them on a common input dataset, absence of ground truth, computational cost of calling orthologs). To address this, the Quest for Orthologs consortium maintains a reference set of proteomes and provides a web server for continuous orthology benchmarking (http://orthology.benchmarkservice.org). Furthermore, consensus ortholog calls derived from public benchmark submissions are provided on the Alliance of Genome Resources website, the joint portal of NIH-funded model organism databases.

Nucleosome Dynamics: a new tool for the dynamic analysis of nucleosome positioning.

We present Nucleosome Dynamics, a suite of programs integrated into a virtual research environment and created to define nucleosome architecture and dynamics from noisy experimental data. The package allows both the definition of nucleosome architectures and the detection of changes in nucleosomal organization due to changes in cellular conditions. Results are displayed in the context of genomic information thanks to different visualizers and browsers, allowing the user a holistic, multidimensional view of the genome/transcriptome. The package shows good performance for both locating equilibrium nucleosome architecture and nucleosome dynamics and provides abundant useful information in several test cases, where experimental data on nucleosome position (and for some cases expression level) have been collected for cells under different external conditions (cell cycle phase, yeast metabolic cycle progression, changes in nutrients or difference in MNase digestion level). Nucleosome Dynamics is a free software and is provided under several distribution models.

BioExcel Building Blocks, a software library for interoperable biomolecular simulation workflows.

In the recent years, the improvement of software and hardware performance has made biomolecular simulations a mature tool for the study of biological processes. Simulation length and the size and complexity of the analyzed systems make simulations both complementary and compatible with other bioinformatics disciplines. However, the characteristics of the software packages used for simulation have prevented the adoption of the technologies accepted in other bioinformatics fields like automated deployment systems, workflow orchestration, or the use of software containers. We present here a comprehensive exercise to bring biomolecular simulations to the "bioinformatics way of working". The exercise has led to the development of the BioExcel Building Blocks (BioBB) library. BioBB's are built as Python wrappers to provide an interoperable architecture. BioBB's have been integrated in a chain of usual software management tools to generate data ontologies, documentation, installation packages, software containers and ways of integration with workflow managers, that make them usable in most computational environments.

Genetic association between CD96 locus and immunogenicity to anti-TNF therapy in Crohn's disease.

The production of antibodies to anti-tumor necrosis factor alpha (TNF) agents is one of the main causes of treatment failure in Crohn's disease (CD). To date, however, the contribution of genetics to anti-TNF immunogenicity in CD is still unknown. The objective of the present study was to identify genetic variation associated with anti-TNF immunogenicity in CD. We performed a two-stage genome-wide association study in a cohort of 96 and 123 adalimumab-treated patients, respectively. In the discovery stage, we identified a genome-wide significant association between the CD96 locus and the production of antibodies to anti-TNF treatment (P = 1.88e-09). This association was validated in the replication stage (P < 0.05). The risk allele for anti-TNF immunogenicity was found to be also associated with a lack of response to anti-TNF therapy (P = 0.019). These findings represent an important step toward the understanding of the immunogenicity-based mechanisms that underlie anti-TNF response in CD.

A genome-wide association study identifies SLC8A3 as a susceptibility locus for ACPA-positive rheumatoid arthritis.

OBJECTIVE: RA patients with serum ACPA have a strong and specific genetic background. The objective of the study was to identify new susceptibility genes for ACPA-positive RA using a genome-wide association approach. METHODS: A total of 924 ACPA-positive RA patients with joint damage in hands and/or feet, and 1524 healthy controls were genotyped in 582 591 single-nucleotide polymorphisms (SNPs) in the discovery phase. In the validation phase, the most significant SNPs in the genome-wide association study representing new candidate loci for RA were tested in an independent cohort of 863 ACPA-positive patients with joint damage and 1152 healthy controls. All individuals from the discovery and validation cohorts were Caucasian and of Southern European ancestry. RESULTS: In the discovery phase, 60 loci not previously associated with RA risk showed evidence for association at P < 5×10(-4) and were tested for replication in the validation cohort. A total of 12 loci were replicated at the nominal level (P < 0.05, same direction of effect as in the discovery phase). When combining the discovery and validation cohorts, an intronic SNP in the Solute Carrier family 8 gene (SLC8A3) was found to be associated with ACPA-positive RA at a genome-wide level of significance RA [odds ratio (95% CI): 1.42 (1.25, 1.6), Pcombined = 3.19×10(-8)]. CONCLUSIONS: SLC8A3 was identified as a new risk locus for ACPA-positive RA. This study demonstrates the advantage of analysing relevant subsets of RA patients to identify new genetic risk variants.

Identification of IRX1 as a Risk Locus for Rheumatoid Factor Positivity in Rheumatoid Arthritis in a Genome-Wide Association Study.

OBJECTIVE: Rheumatoid factor (RF) is a well-established diagnostic and prognostic biomarker in rheumatoid arthritis (RA). However, ∼20% of RA patients are negative for this anti-IgG antibody. To date, only variation at the HLA-DRB1 gene has been associated with the presence of RF. This study was undertaken to identify additional genetic variants associated with RF positivity. METHODS: A genome-wide association study (GWAS) for RF positivity was performed using an Illumina Quad610 genotyping platform. A total of 937 RF-positive and 323 RF-negative RA patients were genotyped for >550,000 single-nucleotide polymorphisms (SNPs). Association testing was performed using an allelic chi-square test implemented in Plink software. An independent cohort of 472 RF-positive and 190 RF-negative RA patients was used to validate the most significant findings. RESULTS: In the discovery stage, a SNP in the IRX1 locus on chromosome 5p15.3 (SNP rs1502644) showed a genome-wide significant association with RF positivity (P = 4.13 × 10(-8) , odds ratio [OR] 0.37 [95% confidence interval (95% CI) 0.26-0.53]). In the validation stage, the association of IRX1 with RF was replicated in an independent group of RA patients (P = 0.034, OR 0.58 [95% CI 0.35-0.97] and combined P = 1.14 × 10(-8) , OR 0.43 [95% CI 0.32-0.58]). CONCLUSION: To our knowledge, this is the first GWAS of RF positivity in RA. Variation at the IRX1 locus on chromosome 5p15.3 is associated with the presence of RF. Our findings indicate that IRX1 and HLA-DRB1 are the strongest genetic factors for RF production in RA.

Genome-Wide Pathway Analysis Identifies Genetic Pathways Associated with Psoriasis.

Psoriasis is a chronic inflammatory disease with a complex genetic architecture. To date, the psoriasis heritability is only partially explained. However, there is increasing evidence that the missing heritability in psoriasis could be explained by multiple genetic variants of low effect size from common genetic pathways. The objective of this study was to identify new genetic variation associated with psoriasis risk at the pathway level. We genotyped 598,258 single nucleotide polymorphisms in a discovery cohort of 2,281 case-control individuals from Spain. We performed a genome-wide pathway analysis using 1,053 reference biological pathways. A total of 14 genetic pathways (PFDR ≤ 2.55 × 10(-2)) were found to be significantly associated with psoriasis risk. Using an independent validation cohort of 7,353 individuals from the UK, a total of 6 genetic pathways were significantly replicated (PFDR ≤ 3.46 × 10(-2)). We found genetic pathways that had not been previously associated with psoriasis risk such as retinol metabolism (Pcombined = 1.84 × 10(-4)), the transport of inorganic ions and amino acids (Pcombined = 1.57 × 10(-7)), and post-translational protein modification (Pcombined = 1.57 × 10(-7)). In the latter pathway, MGAT5 showed a strong network centrality, and its association with psoriasis risk was further validated in an additional case-control cohort of 3,429 individuals (P < 0.05). These findings provide insights into the biological mechanisms associated with psoriasis susceptibility.

BIGNASim: a NoSQL database structure and analysis portal for nucleic acids simulation data.

Molecular dynamics simulation (MD) is, just behind genomics, the bioinformatics tool that generates the largest amounts of data, and that is using the largest amount of CPU time in supercomputing centres. MD trajectories are obtained after months of calculations, analysed in situ, and in practice forgotten. Several projects to generate stable trajectory databases have been developed for proteins, but no equivalence exists in the nucleic acids world. We present here a novel database system to store MD trajectories and analyses of nucleic acids. The initial data set available consists mainly of the benchmark of the new molecular dynamics force-field, parmBSC1. It contains 156 simulations, with over 120 µs of total simulation time. A deposition protocol is available to accept the submission of new trajectory data. The database is based on the combination of two NoSQL engines, Cassandra for storing trajectories and MongoDB to store analysis results and simulation metadata. The analyses available include backbone geometries, helical analysis, NMR observables and a variety of mechanical analyses. Individual trajectories and combined meta-trajectories can be downloaded from the portal. The system is accessible through http://mmb.irbbarcelona.org/BIGNASim/. Supplementary Material is also available on-line at http://mmb.irbbarcelona.org/BIGNASim/SuppMaterial/.

Inntags: small self-structured epitopes for innocuous protein tagging.

Protein tagging is widely used in approaches ranging from affinity purification to fluorescence-based detection in live cells. However, an intrinsic limitation of tagging is that the native function of the protein may be compromised or even abolished by the presence of the tag. Here we describe and characterize a set of small, innocuous protein tags (inntags) that we anticipate will find application in a variety of biological techniques.

A deletion at ADAMTS9-MAGI1 locus is associated with psoriatic arthritis risk.

OBJECTIVE: Copy number variants (CNVs) have been associated with the risk to develop multiple autoimmune diseases. Our objective was to identify CNVs associated with the risk to develop psoriatic arthritis (PsA) using a genome-wide analysis approach. METHODS: A total of 835 patients with PsA and 1498 healthy controls were genotyped for CNVs using the Illumina HumanHap610 BeadChip genotyping platform. Genomic CNVs were characterised using CNstream analysis software and analysed for association using the χ(2) test. The most significant genomic CNV associations with PsA risk were independently tested in a validation sample of 1133 patients with PsA and 1831 healthy controls. In order to test for the specificity of the variants with PsA aetiology, we also analysed the association to a cohort of 822 patients with purely cutaneous psoriasis (PsC). RESULTS: A total of 165 common CNVs were identified in the genome-wide analysis. We found a highly significant association of an intergenic deletion between ADAMTS9 and MAGI1 genes on chromosome 3p14.1 (p=0.00014). Using the independent patient and control cohort, we validated the association between ADAMTS9-MAGI1 deletion and PsA risk (p=0.032). Using next-generation sequencing, we characterised the 26 kb associated deletion. Finally, analysing the PsC cohort we found a lower frequency of the deletion compared with the PsA cohort (p=0.0088) and a similar frequency to that of healthy controls (p>0.3). CONCLUSIONS: The present genome-wide scan for CNVs associated with PsA risk has identified a new deletion associated with disease risk and which is also differential from PsC risk.

A genome-wide association study on a southern European population identifies a new Crohn's disease susceptibility locus at RBX1-EP300.

OBJECTIVE: Genome-wide association studies (GWAS) have identified multiple risk loci for Crohn's disease (CD). However, the cumulative risk exerted by these loci is low, and the likelihood that additional, as-yet undiscovered loci contribute to the risk of CD is very high. We performed a GWAS on a southern European population to identify new CD risk loci. DESIGN: We genotyped 620 901 genome markers on 1341 CD patients and 1518 controls from Spain. The top association signals representing new candidate risk loci were subsequently analysed in an independent replication cohort of 1365 CD patients and 1396 controls. RESULTS: We identified a genome-wide significant association on chromosome 22q13.2 in the intergenic region between the RBX1 and EP300 genes (single nucleotide polymorphism rs4820425, OR 1.27, 95% CI 1.17 to 1.38, p=3.42E-8). We also found suggestive evidence for the association of the IFNGR2 (21q22.11), FOXP2 (7q31), MACROD2 (20p12.1) and AIF1 (6p21.3) loci with CD risk. CONCLUSIONS: In this GWAS performed on a southern European cohort, we have identified a new risk locus for CD between RBX1 and EP300. This study demonstrates that using populations of different ancestry is a useful strategy to identify new risk loci for CD.