Similar Datasets
Project description:Genetic variants, including mobile element insertions (MEIs), are known to impact the epigenome. We hypothesized that the use of a genome graph, which encapsulates genetic diversity, could reveal missing epigenomic signal. We tested this in a dataset obtained by sequencing the epigenome of monocyte-derived macrophages from 35 ancestrally diverse individuals before and after Influenza virus infection, which also allowed us to investigate the potential role of MEIs in immunity. After characterizing genetic variants in this cohort using linked-reads, including 5140 Alu, 316 L1, 94 SVAs and 48 ERVs, we incorporated them into a genome graph. Mapping epigenetic data to this graph revealed 2.5%, 3.0% and 2.3% novel peaks for H3K4me1 and H3K27ac ChIP-seq and ATAC-seq respectively. Notably, using a genome graph also modified quantitative trait loci estimates and we observed 375 polymorphic MEIs in active epigenomic state. For example, we found an AluYh3 polymorphism whose chromatin state changed after infection and that was associated with the expression of TRIM25, a gene that restricts influenza RNA synthesis. Our results demonstrate that graph genomes can reveal regulatory regions that would have been overlooked by other approaches.
2023-02-21 | GSE225704 | GEO
Project description:Genetic variants, including mobile element insertions (MEIs), are known to impact the epigenome. We hypothesized that the use of a genome graph, which encapsulates genetic diversity, could reveal missing epigenomic signal. We tested this in a dataset obtained by sequencing the epigenome of monocyte-derived macrophages from 35 ancestrally diverse individuals before and after Influenza virus infection, which also allowed us to investigate the potential role of MEIs in immunity. After characterizing genetic variants in this cohort using linked-reads, including 5140 Alu, 316 L1, 94 SVAs and 48 ERVs, we incorporated them into a genome graph. Mapping epigenetic data to this graph revealed 2.5%, 3.0% and 2.3% novel peaks for H3K4me1 and H3K27ac ChIP-seq and ATAC-seq respectively. Notably, using a genome graph also modified quantitative trait loci estimates and we observed 375 polymorphic MEIs in active epigenomic state. For example, we found an AluYh3 polymorphism whose chromatin state changed after infection and that was associated with the expression of TRIM25, a gene that restricts influenza RNA synthesis. Our results demonstrate that graph genomes can reveal regulatory regions that would have been overlooked by other approaches.
2023-02-21 | GSE225706 | GEO
Project description:Influenza A virus (IAV) is a major respiratory pathogen of both humans and animals. The lung is protected from pathogens by alveolar epithelial cells, tissue-resident alveolar macrophages, dendritic cells, and mast cells. The role of alveolar epithelial cells, endothelial cells, and alveolar macrophages during IAV infection has been studied previously. In this study, we address the role of mast cells during IAV infection. Respiratory infection with A/WSN/33 causes significant disease and immunopathology in C57BL/6 mice but not in B6.Cg-Kit(W-sh) mice, which lack mast cells. During in vitro coculture, A/WSN/33 caused mast cells to release histamine, secrete cytokines and chemokines, and produce leukotrienes. Moreover, when mast cells were infected with IAV, the virus did not replicate within mast cells. Importantly, human H1N1, H3N2, and influenza B virus isolates also could activate mast cells in vitro. Mast cell production of cytokines and chemokines occurs in a RIG-I/MAVS-dependent mechanism; in contrast, histamine production occurred through a RIG-I/MAVS-independent mechanism. Our data highlight that, following IAV infection, the response of mast cells is controlled by multiple receptors. In conclusion, we identified a unique inflammatory cascade activated during IAV infection that could potentially be targeted to limit morbidity following IAV infection.
| S-EPMC3633673 | biostudies-literature
Project description:BackgroundCertain hand activities cause deformation and displacement of the median nerve at the carpal tunnel due to the gliding motion of tendons surrounding it. As smartphone usage escalates, this raises the public's concern whether hand activities while using smartphones can lead to median nerve problems.ObjectiveThe aims of this study were to 1) develop kinematic graphs and 2) investigate the associated deformation and rotational information of median nerve in the carpal tunnel during hand activities.MethodsDominant wrists of 30 young adults were examined with ultrasonography by placing a transducer transversely on their wrist crease. Ultrasound video clips were recorded when the subject performing 1) thumb opposition with the wrist in neutral position, 2) thumb opposition with the wrist in ulnar deviation and 3) pinch grip with the wrist in neutral position. Six still images that were separated by 0.2-second intervals were then captured from the ultrasound video for the determination of 1) cross-sectional area (CSA), 2) flattening ratio (FR), 3) rotational displacement (RD) and 4) translational displacement (TD) of median nerve in the carpal tunnel, and these collected information of deformation, rotational and displacement of median nerve were compared between 1) two successive time points during a single hand activity and 2) different hand motions at the same time point. Finally, kinematic graphs were constructed to demonstrate the mobility of median nerve during different hand activities.ResultsPerforming different hand activities during this study led to a gradual reduction in CSA of the median nerve, with thumb opposition together with the wrist in ulnar deviation causing the greatest extent of deformation of the median nerve. Thumb opposition with the wrist in ulnar deviation also led to the largest extent of TD when compared to the other two hand activities of this study. Kinematic graphs showed that the motion pathways of median nerve during different hand activities were complex.ConclusionWe observed that the median nerve in the carpal tunnel was rotated, deformed and displaced during the hand activities that people may be performed when using a smartphone, suggesting an increased risk of carpal tunnel syndrome (CTS). In addition, the kinematic graphs of median nerve developed in the present study provide new clues for further studies on the pathophysiology of CTS, and alerting smartphone users to establish proper postural habits when using handheld electronic devices.
| S-EPMC4930216 | biostudies-literature
Project description:Chromatin is the tightly packaged structure of DNA and protein within the nucleus of a cell. The arrangement of different protein complexes along the DNA modulates and is modulated by gene expression. Measuring the binding locations and level of occupancy of different transcription factors (TFs) and nucleosomes is therefore crucial to understanding gene regulation. Antibody-based methods for assaying chromatin occupancy are capable of identifying the binding sites of specific DNA binding factors, but only one factor at a time. On the other hand, epigenomic accessibility data like ATAC-seq, DNase-seq, and MNase-seq provide insight into the chromatin landscape of all factors bound along the genome, but with minimal insight into the identities of those factors. Here, we present RoboCOP, a multivariate state space model that integrates chromatin information from epigenomic accessibility data with nucleotide sequence to compute genome-wide probabilistic scores of nucleosome and TF occupancy, for hundreds of different factors at once. RoboCOP can be applied to any epigenomic dataset that provides quantitative insight into chromatin accessibility in any organism, but here we apply it to MNase-seq data to elucidate the protein-binding landscape of nucleosomes and 150 TFs across the yeast genome. Using available protein-binding datasets from the literature, we show that our model more accurately predicts the binding of these factors genome-wide.
| S-EPMC8356533 | biostudies-literature
Project description:To gain insight into the evolution of influenza A viruses (IAVs) during infection of vaccinated pigs, we experimentally infected a 3-week-old naive pig with a triple-reassortant H1N1 IAV and placed the seeder pig in direct contact with a group of age-matched vaccinated pigs (n = 10). We indexed the genetic diversity and evolution of the virus at an intra-host level by deep sequencing the entire genome directly from nasal swabs collected at two separate samplings during infection. We obtained 13 IAV metagenomes from 13 samples, which included the virus inoculum and two samples from each of the six pigs that tested positive for IAV during the study. The infection produced a population of heterogeneous alleles (sequence variants) that was dynamic over time. Overall, 794 polymorphisms were identified amongst all samples, which yielded 327 alleles, 214 of which were unique sequences. A total of 43 distinct haemagglutinin proteins were translated, two of which were observed in multiple pigs, whereas the neuraminidase (NA) was conserved and only one dominant NA was found throughout the study. The genetic diversity of IAVs changed dynamically within and between pigs. However, most of the substitutions observed in the internal gene segments were synonymous. Our results demonstrated remarkable IAV diversity, and the complex, rapid and dynamic evolution of IAV during infection of vaccinated pigs that can only be appreciated with repeated sampling of individual animals and deep sequence analysis.
| S-EPMC4857448 | biostudies-literature
Project description:Mixed infection by multiple Mycobacterium tuberculosis (MTB) strains is associated with poor treatment outcome of tuberculosis (TB). Traditional genotyping methods have been used to detect mixed infections of MTB, however, their sensitivity and resolution are limited. Deep whole-genome sequencing (WGS) has been proved highly sensitive and discriminative for studying population heterogeneity of MTB. Here, we developed a phylogenetic-based method to detect MTB mixed infections using WGS data. We collected published WGS data of 782 global MTB strains from public database. We called homogeneous and heterogeneous single nucleotide variations (SNVs) of individual strains by mapping short reads to the ancestral MTB reference genome. We constructed a phylogenomic database based on 68,639 homogeneous SNVs of 652 MTB strains. Mixed infections were determined if multiple evolutionary paths were identified by mapping the SNVs of individual samples to the phylogenomic database. By simulation, our method could specifically detect mixed infections when the sequencing depth of minor strains was as low as 1× coverage, and when the genomic distance of two mixed strains was as small as 16 SNVs. By applying our methods to all 782 samples, we detected 47 mixed infections and 45 of them were caused by locally endemic strains. The results indicate that our method is highly sensitive and discriminative for identifying mixed infections from deep WGS data of MTB isolates.
| S-EPMC4938208 | biostudies-literature
Project description:Mammals can play a role as an intermediate host in the emergence of mammalian-adapted reassortants or mutants of avian influenza A viruses, with pandemic potential. Therefore, detecting viral infection in animals followed by assessment of the hemagglutinin (HA) subtype of the agent is an indispensable process for risk assessment in pandemic preparedness. In this study, we tested the potential of an enzyme-linked immunosorbent assay as a rapid diagnosis method, using a panel of HA subtype antigens. By analyzing reference immune sera, we found that this novel assay could detect HA subtype-specific antibodies without considerable inter-subtypic cross-reactivities, contributing to diagnosis of influenza virus infection.
| S-EPMC6789898 | biostudies-other
Project description:The need to include the genetic variation within a population into a reference genome led to the concept of a genome sequence graph. Nodes of such a graph are labeled with DNA sequences occurring in represented genomes. Due to double-stranded nature of DNA, each node may be oriented in one of two possible ways, resulting in marking one end of the labeling sequence as in-side and the other as out-side. Edges join pairs of sides and reflect adjacency between node sequences in genomes constituting the graph. Linearization of a sequence graph aims at orienting and ordering graph nodes in a way that makes it more efficient for visualization and further analysis, e.g. access and traversal. We propose a new linearization algorithm, called ALIBI - Algorithm for Linearization by Incremental graph BuIlding. The evaluation shows that ALIBI is computationally very efficient and generates high-quality results.
| S-EPMC8264155 | biostudies-literature
Project description:In order to efficiently replicate, viruses require precise interactions with host components and often hijack the host cellular machinery for their own benefit. Several mechanisms involved in protein synthesis and processing are strongly affected and manipulated by viral infections. A better understanding of the interplay between viruses and their host-cell machinery will likely contribute to the development of novel antiviral strategies. Here, we discuss the current knowledge on the interactions between influenza A virus (IAV), the causative agent for most of the annual respiratory epidemics in humans, and the host cellular proteostasis machinery during infection. We focus on the manipulative capacity of this virus to usurp the cellular protein processing mechanisms and further review the protein quality control mechanisms in the cytosol and in the endoplasmic reticulum that are affected by this virus.
| S-EPMC6468813 | biostudies-other