Nuclear envelope disruption triggers hallmarks of aging in lung alveolar macrophages.

Aging is characterized by gradual immune dysfunction and increased disease risk. Genomic instability is considered central to the aging process, but the underlying mechanisms of DNA damage are insufficiently defined. Cells in confined environments experience forces applied to their nucleus, leading to transient nuclear envelope rupture (NER) and DNA damage. Here, we show that Lamin A/C protects lung alveolar macrophages (AMs) from NER and hallmarks of aging. AMs move within constricted spaces in the lung. Immune-specific ablation of lamin A/C results in selective depletion of AMs and heightened susceptibility to influenza virus-induced pathogenesis and lung cancer growth. Lamin A/C-deficient AMs that persist display constitutive NER marks, DNA damage and p53-dependent senescence. AMs from aged wild-type and from lamin A/C-deficient mice share a lysosomal signature comprising CD63. CD63 is required to limit damaged DNA in macrophages. We propose that NER-induced genomic instability represents a mechanism of aging in AMs.

The Promise of Single-Cell RNA Sequencing to Redefine the Understanding of Crohn's Disease Fibrosis Mechanisms.

Crohn's disease (CD) is a chronic inflammatory bowel disease with a high prevalence throughout the world. The development of Crohn's-related fibrosis, which leads to strictures in the gastrointestinal tract, presents a particular challenge and is associated with significant morbidity. There are currently no specific anti-fibrotic therapies available, and so treatment is aimed at managing the stricturing complications of fibrosis once it is established. This often requires invasive and repeated endoscopic or surgical intervention. The advent of single-cell sequencing has led to significant advances in our understanding of CD at a cellular level, and this has presented opportunities to develop new therapeutic agents with the aim of preventing or reversing fibrosis. In this paper, we discuss the current understanding of CD fibrosis pathogenesis, summarise current management strategies, and present the promise of single-cell sequencing as a tool for the development of effective anti-fibrotic therapies.

Single-cell RNA-seq analysis reveals dual sensing of HIV-1 in blood Axl+ dendritic cells.

Sensing of incoming viruses is a pivotal task of dendritic cells (DCs). Human primary blood DCs encompass various subsets that are diverse in their susceptibility and response to HIV-1. The recent identification of the blood Axl+DC subset, endowed with unique capacities to bind, replicate, and transmit HIV-1 prompted us to evaluate its anti-viral response. We demonstrate that HIV-1 induced two main broad and intense transcriptional programs in different Axl+DCs potentially induced by different sensors; an NF-κB-mediated program that led to DC maturation and efficient CD4+ T cell activation, and a program mediated by STAT1/2 that activated type I IFN and ISG responses. These responses were absent from cDC2 exposed to HIV-1 except when viral replication was allowed. Finally, Axl+DCs actively replicating HIV-1 identified by quantification of viral transcripts exhibited a mixed NF-κB/ISG innate response. Our results suggest that the route of HIV-1 entry may dictate different innate sensing pathways by DCs.

iBIS2Analyzer: a web server for a phylogeny-driven coevolution analysis of protein families.

Residue coevolution within and between proteins is used as a marker of physical interaction and/or residue functional cooperation. Pairs or groups of coevolving residues are extracted from multiple sequence alignments based on a variety of computational approaches. However, coevolution signals emerging in subsets of sequences might be lost if the full alignment is considered. iBIS2Analyzer is a web server dedicated to a phylogeny-driven coevolution analysis of protein families with different evolutionary pressure. It is based on the iterative version, iBIS2, of the coevolution analysis method BIS, Blocks in Sequences. iBIS2 is designed to iteratively select and analyse subtrees in phylogenetic trees, possibly large and comprising thousands of sequences. With iBIS2Analyzer, openly accessible at http://ibis2analyzer.lcqb.upmc.fr/, the user visualizes, compares and inspects clusters of coevolving residues by mapping them onto sequences, alignments or structures of choice, greatly simplifying downstream analysis steps. A rich and interactive graphic interface facilitates the biological interpretation of the results.

Single-cell analysis reveals divergent responses of human dendritic cells to the MVA vaccine.

Modified vaccinia Ankara (MVA) is a live, attenuated human smallpox vaccine and a vector for the development of new vaccines against infectious diseases and cancer. Efficient activation of the immune system by MVA partially relies on its encounter with dendritic cells (DCs). MVA infection of DCs leads to multiple outcomes, including cytokine production, activation of costimulatory molecules for T cell stimulation, and cell death. Here, we examined how these diverse responses are orchestrated in human DCs. Single-cell analyses revealed that the response to MVA infection in DCs was limited to early viral gene expression. In response to the early events in the viral cycle, we found that DCs grouped into three distinct clusters. A cluster of infected cells sensed the MVA genome by the intracellular innate immunity pathway mediated by cGAS, STING, TBK1, and IRF3 and subsequently produced inflammatory cytokines. In response to these cytokines, a cluster of noninfected bystander cells increased costimulatory molecule expression. A separate cluster of infected cells underwent caspase-dependent apoptosis. Induction of apoptosis persisted after inhibition of innate immunity pathway mediators independently of previously described IRF-dependent or replication-dependent pathways and was a response to early MVA gene expression. Together, our study identified multiple mechanisms that underlie the interactions of MVA with human DCs.

Macrophages Maintain Epithelium Integrity by Limiting Fungal Product Absorption.

The colon is primarily responsible for absorbing fluids. It contains a large number of microorganisms including fungi, which are enriched in its distal segment. The colonic mucosa must therefore tightly regulate fluid influx to control absorption of fungal metabolites, which can be toxic to epithelial cells and lead to barrier dysfunction. How this is achieved remains unknown. Here, we describe a mechanism by which the innate immune system allows rapid quality check of absorbed fluids to avoid intoxication of colonocytes. This mechanism relies on a population of distal colon macrophages that are equipped with "balloon-like" protrusions (BLPs) inserted in the epithelium, which sample absorbed fluids. In the absence of macrophages or BLPs, epithelial cells keep absorbing fluids containing fungal products, leading to their death and subsequent loss of epithelial barrier integrity. These results reveal an unexpected and essential role of macrophages in the maintenance of colon-microbiota interactions in homeostasis. VIDEO ABSTRACT.

Coevolution analysis of amino-acids reveals diversified drug-resistance solutions in viral sequences: a case study of hepatitis B virus.

The study of mutational landscapes of viral proteins is fundamental for the understanding of the mechanisms of cross-resistance to drugs and the design of effective therapeutic strategies based on several drugs. Antiviral therapy with nucleos(t)ide analogues targeting the hepatitis B virus (HBV) polymerase protein (Pol) can inhibit disease progression by suppression of HBV replication and makes it an important case study. In HBV, treatment may fail due to the emergence of drug-resistant mutants. Primary and compensatory mutations have been associated with lamivudine resistance, whereas more complex mutational patterns are responsible for resistance to other HBV antiviral drugs. So far, all known drug-resistance mutations are located in one of the four Pol domains, called reverse transcriptase. We demonstrate that sequence covariation identifies drug-resistance mutations in viral sequences. A new algorithmic strategy, BIS2TreeAnalyzer, is designed to apply the coevolution analysis method BIS2, successfully used in the past on small sets of conserved sequences, to large sets of evolutionary related sequences. When applied to HBV, BIS2TreeAnalyzer highlights diversified viral solutions by discovering thirty-seven positions coevolving with residues known to be associated with drug resistance and located on the four Pol domains. These results suggest a sequential mechanism of emergence for some mutational patterns. They reveal complex combinations of positions involved in HBV drug resistance and contribute with new information to the landscape of HBV evolutionary solutions. The computational approach is general and can be applied to other viral sequences when compensatory mutations are presumed.

S100A7/Ran-binding protein 9 coevolution in mammals.

S100A7 has been suggested to interact with Ran-binding protein 9. Both proteins are nowadays considered key effectors in immune response. Functional interaction between proteins is ensured by coevolution. The mechanisms of vertebrate coevolution between S100A7 and RanBP9 remain unclear. Several approaches for studying coevolution have been developed. Protein coevolution was inferred by calculating the linear correlation coefficients between inter-protein distance matrices using Mirrortree. We found an overall moderate correlation value (R = 0.53, p < 1e-06). Moreover, owing to the high conservation of RanBP9 protein among vertebrates, we chose to utilize a recent version of Blocks in Sequences (BIS2) algorithm implemented in BIS2Analyzer webserver. A coevolution cluster was identified between the two proteins (p < 8.10e-05). In conclusion, our coevolutionary analysis suggests that amino acid variations may modulate S100A7/RanBP9 interaction with potential pathogenic effects. Such findings could guide further analysis to better elucidate the function of S100A7 and RanBP9 and to design drugs targeting for these molecules in diseases.

The N-Terminal Domain of cGAS Determines Preferential Association with Centromeric DNA and Innate Immune Activation in the Nucleus.

Cytosolic DNA activates cyclic guanosine monophosphate-adenosine monophosphate (cGAMP) synthase (cGAS), an innate immune sensor pivotal in anti-microbial defense, senescence, auto-immunity, and cancer. cGAS is considered to be a sequence-independent DNA sensor with limited access to nuclear DNA because of compartmentalization. However, the nuclear envelope is a dynamic barrier, and cGAS is present in the nucleus. Here, we identify determinants of nuclear cGAS localization and activation. We show that nuclear-localized cGAS synthesizes cGAMP and induces innate immune activation of dendritic cells, although cGAMP levels are 200-fold lower than following transfection with exogenous DNA. Using cGAS ChIP-seq and a GFP-cGAS knockin mouse, we find nuclear cGAS enrichment on centromeric satellite DNA, confirmed by imaging, and to a lesser extent on LINE elements. The non-enzymatic N-terminal domain of cGAS determines nucleo-cytoplasmic localization, enrichment on centromeres, and activation of nuclear-localized cGAS. These results reveal a preferential functional association of nuclear cGAS with centromeres.

NONO Detects the Nuclear HIV Capsid to Promote cGAS-Mediated Innate Immune Activation.

Detection of viruses by innate immune sensors induces protective antiviral immunity. The viral DNA sensor cyclic GMP-AMP synthase (cGAS) is necessary for detection of HIV by human dendritic cells and macrophages. However, synthesis of HIV DNA during infection is not sufficient for immune activation. The capsid protein, which associates with viral DNA, has a pivotal role in enabling cGAS-mediated immune activation. We now find that NONO is an essential sensor of the HIV capsid in the nucleus. NONO protein directly binds capsid with higher affinity for weakly pathogenic HIV-2 than highly pathogenic HIV-1. Upon infection, NONO is essential for cGAS activation by HIV and cGAS association with HIV DNA in the nucleus. NONO recognizes a conserved region in HIV capsid with limited tolerance for escape mutations. Detection of nuclear viral capsid by NONO to promote DNA sensing by cGAS reveals an innate strategy to achieve distinction of viruses from self in the nucleus.

A protein coevolution method uncovers critical features of the Hepatitis C Virus fusion mechanism.

Amino-acid coevolution can be referred to mutational compensatory patterns preserving the function of a protein. Viral envelope glycoproteins, which mediate entry of enveloped viruses into their host cells, are shaped by coevolution signals that confer to viruses the plasticity to evade neutralizing antibodies without altering viral entry mechanisms. The functions and structures of the two envelope glycoproteins of the Hepatitis C Virus (HCV), E1 and E2, are poorly described. Especially, how these two proteins mediate the HCV fusion process between the viral and the cell membrane remains elusive. Here, as a proof of concept, we aimed to take advantage of an original coevolution method recently developed to shed light on the HCV fusion mechanism. When first applied to the well-characterized Dengue Virus (DENV) envelope glycoproteins, coevolution analysis was able to predict important structural features and rearrangements of these viral protein complexes. When applied to HCV E1E2, computational coevolution analysis predicted that E1 and E2 refold interdependently during fusion through rearrangements of the E2 Back Layer (BL). Consistently, a soluble BL-derived polypeptide inhibited HCV infection of hepatoma cell lines, primary human hepatocytes and humanized liver mice. We showed that this polypeptide specifically inhibited HCV fusogenic rearrangements, hence supporting the critical role of this domain during HCV fusion. By combining coevolution analysis and in vitro assays, we also uncovered functionally-significant coevolving signals between E1 and E2 BL/Stem regions that govern HCV fusion, demonstrating the accuracy of our coevolution predictions. Altogether, our work shed light on important structural features of the HCV fusion mechanism and contributes to advance our functional understanding of this process. This study also provides an important proof of concept that coevolution can be employed to explore viral protein mediated-processes, and can guide the development of innovative translational strategies against challenging human-tropic viruses.

Protein-protein interaction specificity is captured by contact preferences and interface composition.

Motivation: Large-scale computational docking will be increasingly used in future years to discriminate protein-protein interactions at the residue resolution. Complete cross-docking experiments make in silico reconstruction of protein-protein interaction networks a feasible goal. They ask for efficient and accurate screening of the millions structural conformations issued by the calculations. Results: We propose CIPS (Combined Interface Propensity for decoy Scoring), a new pair potential combining interface composition with residue-residue contact preference. CIPS outperforms several other methods on screening docking solutions obtained either with all-atom or with coarse-grain rigid docking. Further testing on 28 CAPRI targets corroborates CIPS predictive power over existing methods. By combining CIPS with atomic potentials, discrimination of correct conformations in all-atom structures reaches optimal accuracy. The drastic reduction of candidate solutions produced by thousands of proteins docked against each other makes large-scale docking accessible to analysis. Availability and implementation: CIPS source code is freely available at http://www.lcqb.upmc.fr/CIPS. Contact: alessandra.carbone@lip6.fr. Supplementary information: Supplementary data are available at Bioinformatics online.

BIS2Analyzer: a server for co-evolution analysis of conserved protein families.

Along protein sequences, co-evolution analysis identifies residue pairs demonstrating either a specific co-adaptation, where changes in one of the residues are compensated by changes in the other during evolution or a less specific external force that affects the evolutionary rates of both residues in a similar magnitude. In both cases, independently of the underlying cause, co-evolutionary signatures within or between proteins serve as markers of physical interactions and/or functional relationships. Depending on the type of protein under study, the set of available homologous sequences may greatly differ in size and amino acid variability. BIS2Analyzer, openly accessible at http://www.lcqb.upmc.fr/BIS2Analyzer/, is a web server providing the online analysis of co-evolving amino-acid pairs in protein alignments, especially designed for vertebrate and viral protein families, which typically display a small number of highly similar sequences. It is based on BIS2, a re-implemented fast version of the co-evolution analysis tool Blocks in Sequences (BIS). BIS2Analyzer provides a rich and interactive graphical interface to ease biological interpretation of the results.

Chimera: a Bioconductor package for secondary analysis of fusion products.

SUMMARY: Chimera is a Bioconductor package that organizes, annotates, analyses and validates fusions reported by different fusion detection tools; current implementation can deal with output from bellerophontes, chimeraScan, deFuse, fusionCatcher, FusionFinder, FusionHunter, FusionMap, mapSplice, Rsubread, tophat-fusion and STAR. The core of Chimera is a fusion data structure that can store fusion events detected with any of the aforementioned tools. Fusions are then easily manipulated with standard R functions or through the set of functionalities specifically developed in Chimera with the aim of supporting the user in managing fusions and discriminating false-positive results.

GapFiller: a de novo assembly approach to fill the gap within paired reads.

BACKGROUND: Next Generation Sequencing technologies are able to provide high genome coverages at a relatively low cost. However, due to limited reads' length (from 30 bp up to 200 bp), specific bioinformatics problems have become even more difficult to solve. De novo assembly with short reads, for example, is more complicated at least for two reasons: first, the overall amount of "noisy" data to cope with increased and, second, as the reads' length decreases the number of unsolvable repeats grows. Our work's aim is to go at the root of the problem by providing a pre-processing tool capable to produce (in-silico) longer and highly accurate sequences from a collection of Next Generation Sequencing reads. RESULTS: In this paper a seed-and-extend local assembler is presented. The kernel algorithm is a loop that, starting from a read used as seed, keeps extending it using heuristics whose main goal is to produce a collection of error-free and longer sequences. In particular, GapFiller carefully detects reliable overlaps and operates clustering similar reads in order to reconstruct the missing part between the two ends of the same insert. Our tool's output has been validated on 24 experiments using both simulated and real paired reads datasets. The output sequences are declared correct when the seed-mate is found. In the experiments performed, GapFiller was able to extend high percentages of the processed seeds and find their mates, with a false positives rate that turned out to be nearly negligible. CONCLUSIONS: GapFiller, starting from a sufficiently high short reads coverage, is able to produce high coverages of accurate longer sequences (from 300 bp up to 3500 bp). The procedure to perform safe extensions, together with the mate-found check, turned out to be a powerful criterion to guarantee contigs' correctness. GapFiller has further potential, as it could be applied in a number of different scenarios, including the post-processing validation of insertions/deletions detection pipelines, pre-processing routines on datasets for de novo assembly pipelines, or in any hierarchical approach designed to assemble, analyse or validate pools of sequences.