PredIG: a predictor of T-cell immunogenicity

The identification of immunogenic epitopes (such as fragments of proteins, in particular peptides, that can trigger an immune response) is a fundamental need for immune-based therapies. A computational tool that could predict such immunogenic epitopes would have vast potential applications in biomedicine ranging, from vaccine design against viruses or bacteria to therapeutic vaccination of cancer patients. While there are several methods that predict whether a peptide will be shown to the immune system via the Human Leukocyte Antigen (HLA) proteins of a patient, most of them cannot predict whether such presentation will indeed trigger an immune response. Additionally, T-cell immunogenicity is determined by multiple cellular processes, some of which are often overlooked by the current state-of-the-art immunogenicity predictors. The aim of this project is to build PredIG, an immunogenicity predictor that discriminates immunogenic from non-immunogenic T-cell epitopes given the peptide sequence and the HLA typing. After a careful study of the drivers of antigen processing and presentation on HLA class I molecules and an assessment of the physicochemical factors influencing epitope recognition by T-cell receptors (TCRs), we have used a selection of publicly available tools and in-house developed algorithms to identify the most relevant features that determine epitope immunogenicity. We then used these features to build an immunogenicity predictor (PredIG) modelled by XGBoost against immunogenically validated epitopes by the ImmunoEpitope DataBase (IEDB)(1), the PRIME dataset(2) and the TANTIGEN database(3). Pondering the feature importance in the model, the in-house developed softwares, NOAH for HLA Binding Affinity and NetCleave for Proteasomal Processing were identified as the major contributors to the performance of the model. Once PredIG was developed, we benchmarked the capacity to predict the immunogenicity of validated T-cell epitopes versus a set of state-of-the-art methods (Fig.1). Relevantly, PredIG showed a greater performance than the Immunogenicity predictors from Prime(2) and IEDB(4). Additionally, our results confirm that predicting T-cell immunogenicity based on data from T-cell assays is more accurate than using HLA Binding assays, the method mostly used in the field. An AUC value of 0.67 and an enrichment factor in the TOP10 epitopes of 90% outperforms the predictive performance of the available methods. In the context of the immune response against cancers, Tcell immunogenicity of tumoral mutations has been described as a response biomarker for immunotherapies such as immune checkpoint inhibitors. Similarly, the presence of immune infiltrate in a tumor has been related to a better prognosis for many cancer types. What is missing is the link between T-cell immunogenicity of tumoral mutations and the capacity of a tumor to attract immune cells. For this reason, we correlated the PredIG immunogenicity score obtained in a dataset of the The Cancer Genome Atlas (TCGA) against the tumor infiltrate in such tumors demonstrating that rather the total number of mutations a tumor accumulates, the tumor mutation burden (TMB), it is the number of immunogenic mutations what should be accounted for as biomarker of response

Intermittent Connectivity Maintenance With Heterogeneous Robots

We consider a scenario of cooperative task servicing, with a team of heterogeneous robots with different maximum speeds and communication radii, in charge of keeping the network intermittently connected. We abstract the task locations into a $1D$ cycle graph that is traversed by the communicating robots, and we discuss intermittent communication strategies so that each task location is periodically visited, with a worst--case revisiting time. Robots move forward and backward along the cycle graph, exchanging data with their previous and next neighbors when they meet, and updating their region boundaries. Asymptotically, each robot is in charge of a region of the cycle graph, depending on its capabilities. The method is distributed, and robots only exchange data when they meet

Intermittent connectivity maintenance with heterogeneous robots

In this article, we consider a scenario of cooperative task servicing, with a team of heterogeneous robots with different maximum speeds and communication radii, in charge of keeping the network intermittently connected. We abstract the task locations into a one-dimensional cycle graph that is traversed by the communicating robots, and we discuss intermittent communication strategies so that each task location is periodically visited, with a worst-case revisiting time. Robots move forward and backward along the cycle graph, exchanging data with their previous and next neighbors when they meet, and updating their region boundaries. Asymptotically, each robot is in charge of a region of the cycle graph, depending on its capabilities. The method is distributed, and robots only exchange data when they meet

Physical activity, sitting time, and mortality from inflammatory diseases in older adults

Objective: The aim of this study was to examine the independent and combined associations of physical activity (PA) and sitting time (ST) with long-term mortality attributed to inflammatory causes other than cardiovascular disease (CVD) and cancer in a national cohort of older adults in Spain. Design: Prospective study. Setting and Participants: A cohort of 3,677 individuals (1,626 men) aged =60 years was followed-up during 14.3 years. Measures: At baseline, individuals reported PA and ST. The study outcome was death from inflammatory diseases when CVD or cancer mortality was excluded. This outcome was classified into infectious and non-infectious conditions. Analyses were performed with Cox regression and adjusted for PA, ST, and other main confounders (age, sex, educational level, smoking, alcohol consumption, body mass index, and chronic conditions). Results: During follow-up, 286 deaths from inflammatory diseases (77 from infectious diseases) were identified. Compared to individuals who defined themselves as inactive/less active, mortality from inflammatory diseases was lower in those who were moderately active (hazard ratio [HR] = 0.67, 95% confidence interval [CI] = 0.50-0.90) or very active (HR = 0.48, 95%CI = 0.33-0.68), independently of ST. Also, being seated ≥7 h/d vs. < 7 h/d was linked to higher mortality (HR = 1.38, 95%CI = 1.02-1.87). The largest risk of mortality was observed in inactive/less active individuals with ST≥7 h/d (HR = 2.29, 95%CI = 1.59-3.29) compared to those with moderate/very PA and ST < 7 h/d. Low PA and high ST were consistently associated with a higher risk of mortality from non-infectious inflammatory causes. Associations of PA and ST with mortality from infectious inflammatory causes showed a similar trend, but most of them did not reach statistical significance. Conclusions: Low PA and high ST were independently associated with higher mortality from inflammatory diseases other than CVD or cancer in older adults. Interventions addressing simultaneously both behaviors could have greater benefits than those focusing on only one of themThis work was supported by FIS grant 16/609 (Instituto de Salud Carlos III, State Secretary of R+D+I and FEDER/FSE), MINECO R+D+I grant (DEP2013-47786-R), MECD mobility grant (JC2015-00080), the FRAILOMIC Initiative (European Union FP7-HEALTH-2012-Proposal No. 305483-2), and the ATHLOS project (European project H2020- Project ID: 635316

Porphyrin Binding to Gun4 Protein, Facilitated by a Flexible Loop, Controls Metabolite Flow through the Chlorophyll Biosynthetic Pathway.

In oxygenic phototrophs, chlorophylls, hemes, and bilins are synthesized by a common branched pathway. Given the phototoxic nature of tetrapyrroles, this pathway must be tightly regulated, and an important regulatory role is attributed to magnesium chelatase enzyme at the branching between the heme and chlorophyll pathway. Gun4 is a porphyrin-binding protein known to stimulate in vitro the magnesium chelatase activity, but how the Gun4-porphyrin complex acts in the cell was unknown. To address this issue, we first performed simulations to determine the porphyrin-docking mechanism to the cyanobacterial Gun4 structure. After correcting crystallographic loop contacts, we determined the binding site for magnesium protoporphyrin IX. Molecular modeling revealed that the orientation of α6/α7 loop is critical for the binding, and the magnesium ion held within the porphyrin is coordinated by Asn-211 residue. We also identified the basis for stronger binding in the Gun4-1 variant and for weaker binding in the W192A mutant. The W192A-Gun4 was further characterized in magnesium chelatase assay showing that tight porphyrin binding in Gun4 facilitates its interaction with the magnesium chelatase ChlH subunit. Finally, we introduced the W192A mutation into cells and show that the Gun4-porphyrin complex is important for the accumulation of ChlH and for channeling metabolites into the chlorophyll biosynthetic pathway

Previous SARS-CoV-2 Infection Increases B.1.1.7 Cross-Neutralization by Vaccinated Individuals

With the spread of new variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is a need to assess the protection conferred by both previous infections and current vaccination. Here we tested the neutralizing activity of infected and/or vaccinated individuals against pseudoviruses expressing the spike of the original SARS-CoV-2 isolate Wuhan-Hu-1 (WH1), the D614G mutant and the B.1.1.7 variant. Our data show that parameters of natural infection (time from infection and nature of the infecting variant) determined cross-neutralization. Uninfected vaccinees showed a small reduction in neutralization against the B.1.1.7 variant compared to both the WH1 strain and the D614G mutant. Interestingly, upon vaccination, previously infected individuals developed more robust neutralizing responses against B.1.1.7, suggesting that vaccines can boost the neutralization breadth conferred by natural infection

Heterogeneous Infectivity and Pathogenesis of SARS-CoV-2 Variants Beta, Delta and Omicron in Transgenic K18-hACE2 and Wildtype Mice

The emerging SARS-CoV-2 variants of concern (VOCs) may display enhanced transmissibility, more severity and/or immune evasion; however, the pathogenesis of these new VOCs in experimental SARS-CoV-2 models or the potential infection of other animal species is not completely understood. Here we infected K18-hACE2 transgenic mice with B.1, B.1.351/Beta, B.1.617.2/Delta and BA.1.1/Omicron isolates and demonstrated heterogeneous infectivity and pathogenesis. B.1.351/Beta variant was the most pathogenic, while BA.1.1/Omicron led to lower viral RNA in the absence of major visible clinical signs. In parallel, we infected wildtype (WT) mice and confirmed that, contrary to B.1 and B.1.617.2/Delta, B.1.351/Beta and BA.1.1/Omicron can infect them. Infection in WT mice coursed without major clinical signs and viral RNA was transient and undetectable in the lungs by day 7 post-infection. In silico modeling supported these findings by predicting B.1.351/Beta receptor binding domain (RBD) mutations result in an increased affinity for both human and murine ACE2 receptors, while BA.1/Omicron RBD mutations only show increased affinity for murine ACE2

Defending the genome from the enemy within:mechanisms of retrotransposon suppression in the mouse germline

The viability of any species requires that the genome is kept stable as it is transmitted from generation to generation by the germ cells. One of the challenges to transgenerational genome stability is the potential mutagenic activity of transposable genetic elements, particularly retrotransposons. There are many different types of retrotransposon in mammalian genomes, and these target different points in germline development to amplify and integrate into new genomic locations. Germ cells, and their pluripotent developmental precursors, have evolved a variety of genome defence mechanisms that suppress retrotransposon activity and maintain genome stability across the generations. Here, we review recent advances in understanding how retrotransposon activity is suppressed in the mammalian germline, how genes involved in germline genome defence mechanisms are regulated, and the consequences of mutating these genome defence genes for the developing germline