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3,441 results for “Immune cells”
T cell cholesterol transport links intestinal immune responses to dietary lipid absorption
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Long COVID manifests with T cell dysregulation, inflammation, and an uncoordinated adaptive immune response to SARS-CoV-2
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Dataset related to article "Single-Cell Sequencing of Mouse Heart Immune Infiltrate in Pressure Overload-Driven Heart Failure Reveals Extent of Immune Activation."
<p>BACKGROUND:</p> <p>Inflammation is a key component of cardiac disease, with macrophages and T lymphocytes mediating essential roles in the progression to heart failure. Nonetheless, little insight exists on other immune subsets involved in the cardiotoxic response.</p> <p>METHODS:</p> <p>Here, we used single-cell RNA sequencing to map the cardiac immune composition in the standard murine nonischemic, pressure-overload heart failure model. By focusing our analysis on CD45<sup>+</sup> cells, we obtained a higher resolution identification of the immune cell subsets in the heart, at early and late stages of disease and in controls. We then integrated our findings using multiparameter flow cytometry, immunohistochemistry, and tissue clarification immunofluorescence in mouse and human.</p> <p>RESULTS:</p> <p>We found that most major immune cell subpopulations, including macrophages, B cells, T cells and regulatory T cells, dendritic cells, Natural Killer cells, neutrophils, and mast cells are present in both healthy and diseased hearts. Most cell subsets are found within the myocardium, whereas mast cells are found also in the epicardium. Upon induction of pressure overload, immune activation occurs across the entire range of immune cell types. Activation led to upregulation of key subset-specific molecules, such as oncostatin M in proinflammatory macrophages and PD-1 in regulatory T cells, that may help explain clinical findings such as the refractivity of patients with heart failure to anti-tumor necrosis factor therapy and cardiac toxicity during anti-PD-1 cancer immunotherapy, respectively.</p> <p>CONCLUSIONS:</p> <p>Despite the absence of infectious agents or an autoimmune trigger, induction of disease leads to immune activation that involves far more cell types than previously thought, including neutrophils, B cells, Natural Killer cells, and mast cells. This opens up the field of cardioimmunology to further investigation by using toolkits that have already been developed to study the aforementioned immune subsets. The subset-specific molecules that mediate their activation may thus become useful targets for the diagnostics or therapy of heart failure.</p> <p> </p> <p>This dataset is created in .ets form, we attach a pdf with the information about.</p>
Dataset related to article "Costimulatory Molecules and Immune Checkpoints Are Differentially Expressed on Different Subsets of Dendritic Cells."
<p>Dendritic cells (DCs) play a crucial role in initiating and shaping immune responses. The effects of DCs on adaptive immune responses depend partly on functional specialization of distinct DC subsets, and partly on the activation state of DCs, which is largely dictated by environmental signals. Fully activated immunostimulatory DCs express high levels of costimulatory molecules, produce pro-inflammatory cytokines, and stimulate T cell proliferation, whereas tolerogenic DCs express low levels of costimulatory molecules, produce immunomodulatory cytokines and impair T cell proliferation. Relevant to the increasing use of immune checkpoint blockade in cancer treatment, signals generated from inhibitory checkpoint molecules on DC surface may also contribute to the inhibitory properties of tolerogenic DCs. Yet, our knowledge on the expression of inhibitory molecules on human DC subsets is fragmentary. Therefore, in this study, we investigated the expression of three immune checkpoints on peripheral blood DC subsets, in basal conditions and upon exposure to pro-inflammatory and anti-inflammatory stimuli, by using a flow cytometric panel that allows a direct comparison of the activatory/inhibitory phenotype of DC-lineage and inflammatory DC subsets. We demonstrated that functionally distinct DC subsets are characterized by differential expression of activatory and inhibitory molecules, and that cDC1s in particular are endowed with a unique immune checkpoint repertoire characterized by high TIM-3 expression, scarce PD-L1 expression and lack of ILT2. Notably, this unique cDC1 repertoire was subverted in a group of patients with myelodysplastic syndromes included in the study. Applied to the characterization of DCs in the tumor microenvironment, this panel has the potential to provide valuable information to be used for investigating the role of DC subsets in cancer, guiding DC-targeting treatments, and possibly identifying predictive biomarkers for clinical response to cancer immunotherapy.</p>
Data from: Social effects on age-related and sex-specific immune cell profiles in a wild mammal
<p>Evidence for age-related changes in innate and adaptive immune responses is increasing in wild populations. Such changes have been linked to fitness, and knowledge of the factors driving immune response variation is important for understanding the evolution of immunity. Age-related changes in immune profiles may be due to factors such as immune system development, sex-specific behaviour and responses to environmental conditions. Social environments may also contribute to variation in immunological responses, for example, through transmission of pathogens and stress arising from resource and mate competition. Yet, the impact of the social environment on age-related changes in immune cell profiles is currently understudied in the wild. Here, we tested the relationship between leukocyte cell composition (proportion of neutrophils and lymphocytes [innate and adaptive immunity, respectively] that were lymphocytes) and age, sex, and group size in a wild population of European badgers (<i>Meles meles</i>). We found that the proportion of lymphocytes in early-life was greater in males in smaller groups compared to larger groups, but with a faster age-related decline in smaller groups. In contrast, the proportion of lymphocytes in females was not significantly related to age or group size. Our results provide evidence of sex-specific age-related changes in immune cell profiles in a wild mammal, which are influenced by the social environment.</p>
The impacts of body mass on immune cell concentrations in birds
<p>Body mass affects many biological traits, but its impacts on immune defenses are fairly unknown. Recent research on mammals found that neutrophil concentrations disproportionately increased (scaled hypermetrically) with body mass, a result not predicted by any existing theory. Although the scaling relationship for mammals might predict how leukocyte concentrations scale with body mass in other vertebrates, vertebrate classes are distinct in many ways that might affect their current and historic interactions with parasites and hence the evolution of their immune systems. Subsequently, here, we asked which existing scaling hypothesis best-predicts relationships between body mass and lymphocyte, eosinophil, and heterophil concentrations—the avian functional equivalent of neutrophils—among >100 species of birds. We then examined the predictive power of body mass relative to life-history variation, as an extensive literature indicates that the timing of key life events has influenced immune system variation among species. Finally, we ask whether avian scaling patterns differ from the patterns we observed in mammals. We found that an intercept-only model best-explained lymphocyte and eosinophil concentrations among birds, indicating that the concentrations of these cell types were both independent of body mass. For heterophils, however, body mass explained 31% of the variation in concentrations among species, much more than life-history variation (4%). As with mammalian neutrophils, avian heterophils scaled hypermetrically (<i>b=</i>0.19 +/- 0.05), but more steeply than mammals (~1.5x; 0.11+/- 0.03). As such, we discuss why birds might require more broadly-protective cells compared to mammals of the same body size. Overall, body mass appears to have strong influences on the architecture of immune systems.</p>
Data from: Human circulating antibody-producing B cell as a predictive measure of mucosal immunity to poliovirus
Background: The "gold standard" for assessing mucosal immunity after vaccination with poliovirus vaccines consists in measuring virus excretion in stool after challenge with oral poliovirus vaccine (OPV). This testing is time and resource intensive, and development of alternative methods is a priority for accelerating polio eradication. We therefore evaluated circulating antibody-secreting cells (ASCs) as a potential means to evaluate mucosal immunity to poliovirus vaccine. Methods: 199 subjects, aged 10 years, and previously immunized repeatedly with OPV, were selected. Subjects were assigned to receive either a booster dose of inactivated poliovirus vaccine (IPV), bivalent OPV (bOPV), or no vaccine. Using a micro-modified whole blood-based ELISPOT assay designed for field setting, circulating poliovirus type-specific IgA- and IgG-ASCs, including gut homing ?4?7+ ASCs, were enumerated on days 0 and 7 after booster immunization. In addition, serum samples collected on days 0, 28 and 56 were tested for neutralizing antibody titers against poliovirus types 1, 2, and 3. Stool specimens were collected on day 28 (day of bOPV challenge), and on days 31, 35 and 42 and processed for poliovirus isolation. Results: An IPV dose elicited blood IgA- and IgG-ASC responses in 84.8 to 94.9% of subjects, respectively. In comparison, a bOPV dose evoked corresponding blood ASC responses in 20.0 to 48.6% of subjects. A significant association was found between IgA- and IgG-ASC responses and serum neutralizing antibody titers for poliovirus type 1, 2, 3 (p<0.001). In the IPV group, ?4?7+ ASCs accounted for a substantial proportion of IgA-ASCs and the proportion of subjects with a positive ?4?7+ IgA-ASC response to poliovirus types 1, 2 and 3 was 62.7%, 89.8% and 45.8%, respectively. A significant association was observed between virus excretion and ?4?7+ IgA- and/or IgG-ASC responses to poliovirus type 3 among immunized children; however, only a weak association was found for type 1 poliovirus. Discussion: Our results suggest that virus-specific blood ASCs, especially for type 3 poliovirus, can serve as surrogate of mucosal immunity after vaccination. Further studies are needed to evaluate the duration of such memory responses and to assess the programmatic utility of this whole blood-based mucosal ASC testing for the polio eradication program.
Data from: The contribution of host cell-directed vs. parasite-directed immunity to the disease and dynamics of malaria infections
<p>Hosts defend themselves against pathogens by mounting an immune response. Fully understanding the immune response as a driver of host disease and pathogen evolution requires a quantitative account of its impact on parasite population dynamics. Here, we use a data-driven modeling approach to quantify the birth and death processes underlying the dynamics of infections of the rodent malaria parasite, <span>Plasmodium chabaudi</span>, and the red blood cells (RBCs) it targets. We decompose the immune response into 3 components, each with a distinct effect on parasite and RBC vital rates, and quantify the relative contribution of each component to host disease and parasite density. Our analysis suggest that these components are deployed in a coordinated fashion to realize distinct resource-directed defense strategies that complement the killing of parasitized cells. Early in the infection, the host deploys a strategy reminiscent of siege and scorched-earth tactics, in which it both destroys RBCs and restricts their supply. Late in the infection, a "juvenilization" strategy, in which turnover of RBCs is accelerated, allows the host to recover from anemia while holding parasite proliferation at bay. By quantifying the impact of immunity on both parasite fitness and host disease. we reveal that phenomena often interpreted as immunopathology may in fact be beneficial to the host. Finally, we show that, across mice, the components of the host response are consistently related to each other, even when infections take qualitatively different trajectories. This suggests the existence of simple rules that govern the immune system's deployment.</p>
ComplexEye - a multi lens array microscope for High-Throughput embedded immune cell migration analysis
<p>This dataset contains raw high-resolution movies of migrating neutrophils, which were recorded using the ComplexEye, an array microscope with 16 independent aberration-corrected glass lenses spaced at the pitch of a 96-well plate. Please see the manuscript "ComplexEye - a multi lens array microscope for High-Throughput embedded immune cell migration analysis" for more information.</p><p>The movies can be assigned to the following figures in the manuscript:</p><ul><li>96-well_plate_movies_n=1_complexeye.zip: Figure 3a</li><li>96-well_plate_movies_n=1_leica.zip: Figure 3a</li><li>384-well_plate_movies_n=1_complexeye.zip: Figure 3b</li><li>384-well_plate_movies_n=16_complexeye.zip: Figure 3c</li><li>R01.zip - R17.zip: Figure 4 and 5</li></ul>
An mRNA-encoded, long-lasting Interleukin-2 restores CD8+ T cell neoantigen immunity in MHC class I-deficient cancers
<ul> <li><strong><span>Cd45Summit-IntgrAllgroups_finalUMAP_simplified_colorordered.RData </span></strong><span>contains all final result of the workflow (data integration and annotation) without subsetting the cell types into the different treatment groups.</span></li> <li><strong><span>Cd45Summit-IntgrAllgroups_finalUMAP_Only_CD8Tcells_subsetted.RData </span></strong><span>contains combined dataset of all present CD8+ T cell types (final UMAP, all annotated), which are subsetted into the four treatment groups.</span></li> <li><strong><span>Cd45Summit-IntgrAllgroups_finalUMAP_Only_ProlifMacros_subsetted.RData </span></strong><span>contains only the proliferating CD8+ T cells, which are subsetted into the four different treatment groups.</span></li> <li><strong><span>Cd45Summit-IntgrAllgroups_forJan_Macors_Gr1to4.RData </span></strong><span>contains only the combined macrophages of the dataset, subsetted into the four treatment groups.</span></li> </ul>
RNA sequencing code associated with Billipp et al. Immunity 2024 - Chat + vs Chat - tuft cells
<p>R code and result for RNA-sequencing analysis comparing <em>Chat(GFP)+ </em>and <em>Chat(GFP)- </em>tuft cells sorted from the small intestine of <em>B6.Chat-GFP</em> mice. Associated with Billipp et al. Immunity 2024 titled "Tuft cell-derived acetylcholine promotes epithelial chloride secretion and intestinal helminth clearance"</p>
RNA sequencing code associated with Billipp et al. Immunity 2024 - Prox vs. distal tuft cells
<p>R code and result for RNA-sequencing analysis comparing tuft cells sorted from the proximal and distal small intestine of mice. Associated with Billipp et al. Immunity 2024 titled "<span>Tuft cell-derived acetylcholine promotes epithelial chloride secretion and intestinal helminth clearance</span>"</p>
Data from: Immune Transcriptional Response in Head Kidney Primary Cell Cultures Isolated from the Three Most Important Species in Chilean Salmonids Aquaculture.
<p>Data from Immune Transcriptional Response in Head Kidney Primary Cell Cultures Isolated from the Three Most Important Species in Chilean Salmonids Aquaculture. Files in .JBN and .xlsx format</p>
Transcriptome analysis of immune-inflammatory regulation in Tremella Fuciformis-derived Polysaccharide reeducated B16 cells subcutaneous model
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Blood memory CD8 T cell phenotypes in lung cancer patients predict immune checkpoint treatment responses
<p>Rscript for figure generation and data analysis:</p> <p>GenerateFigures.R</p> <p> </p> <p>Seurat objects containing processed data after quality control:</p> <p><a href="../api/records/10867209/draft/files/NCCS_For_Zenodo.RDS/content" target="_blank" rel="noopener noreferrer">NCCS_For_Zenodo.RDS</a> - NCCS discovery cohort.</p> <p><a href="../api/records/10867209/draft/files/Pavia_For_Zenodo.RDS/content" target="_blank" rel="noopener noreferrer">Pavia_For_Zenodo.RDS</a> - Pavia validation cohort.</p> <p> </p> <p>RDS files containing DEGs or differentially abundant surface markers:</p> <p>TestResults2Groups.rds - Cell type specific LTR vs Non Responder DEG </p> <p>TestResults2GroupsADT.rds - Cell type specific LTR vs Non Responder differential surface markers</p> <p>TestResults2GroupsLungOnly.rds - Cell type specific LTR vs Non Responder DEG on lung samples only</p> <p>TestResults2GroupsLungOnlyADT.rds - Cell type specific LTR vs Non Responder differential surface markers on lung samples only</p> <p>TestResults3Groups.rds - Cell type specific LTR vs R vs Non Responder differential DEG</p> <p>TestResults3GroupsGeneralADT.rds - Across cell type LTR vs R vs Non Responder differential surface markers</p> <p>TestResults2GroupsGeneralRNA.rds - Across cell type LTR vs Non Responder DEG </p> <p>TestResults2GroupsGeneralADT.rds - Across cell type LTR vs Non Responder differential surface markers</p> <p>TestResults2GroupsLungOnlyGeneralRNA.rds - Across cell type LTR vs Non Responder DEG on lung samples only</p> <p>TestResults2GroupsLungOnlyGeneralADT.rds - Across cell type LTR vs Non Responder differential surface markers on lung samples only</p> <p>TestResults3GroupsGeneralRNA.rds - Across cell type LTR vs R vs Non Responder differential DEG</p> <p>TestResults3GroupsGeneralADT.rds - Across cell type LTR vs R vs Non Responder differential surface markers</p> <p> </p> <p>Logistic regression models trained on the NCCS discovery cohort:</p> <p>PerCellPredictions <CellType> * - Celltype specific models predicting either LTR, R or control group trained on all NCCS samples</p> <p>PerCellPredictions_2Groups_LungOnly <CellType> * - Celltype specific models predicting either LTR or NonResponder group, trained on lung samples only.</p> <p>PerCellPredictions_2Groups_<CellType> * - Celltype specific models predicting either LTR or NonResponder trained on all NCCS samples</p>
Unveiling genetic signatures of immune response in immune-related diseases through single-cell eQTL analysis across diverse conditions
<p><em><strong>Unveiling genetic signatures of immune response in immune-related diseases through single-cell eQTL analysis across diverse conditions</strong></em></p> <p> </p> <p>Tools and scripts were used to generate results in Zhang et al 2024.</p> <p>Supplementary files that were not included in the initial submission.</p> <p>Full summary statistics of eQTLs including top eQTLs and all SNP-gene pairs of each cell type, consistent.tar.gz for consistent eQTLs per cell and response.tar.gz for response eQTLs, respectively.</p>
Long-term memory T cells as preventive anticancer immunity elicited by TuA-derived heteroclitic peptides
<p>The host’s immune system may be primed against antigens during the lifetime (e.g. microorganisms antigens—MoAs), and swiftly<br> recalled upon growth of a tumor expressing antigens similar in sequence and structure. C57BL/6 mice were immunized in a preventive<br> setting with tumor antigens (TuAs) or corresponding heteroclitic peptides specific for TC-1 and B16 cell lines. AQ1 Immediately or 2-<br> months after the end of the vaccination protocol, animals were implanted with cell lines. The specific anti-vaccine immune response as<br> well as tumor growth were regularly evaluated for 2 months post-implantation. The preventive vaccination with TuA or their<br> heteroclitic peptides (hPep) was able to delay (B16) or completely suppress (TC-1) tumor growth when cancer cells were implanted<br> immediately after the end of the vaccination. More importantly, TC-1 tumor growth was significantly delayed, and suppressed in 6/8<br> animals, also when cells were implanted 2-months after the end of the vaccination. The vaccine-specific T cell response provided a<br> strong immune correlate to the pattern of tumor growth. A preventive immunization with heteroclitic peptides resembling a TuA is able<br> to strongly delay or even suppress tumor growth in a mouse model. More importantly, the same effect is observed also when tumor<br> cells are implanted 2 months after the end of vaccination, which corresponds to 8 – 10 years in human life. The observed potent tumor<br> control indicates that a memory T cell immunity elicited during the lifetime by a antigens similar to a TuA, i.e. viral antigens, may<br> ultimately represent a great advantage for cancer patients and may lead to a novel preventive anti-cancer vaccine strategy.</p>
Differences in local immune cell landscape between Q fever and atherosclerotic abdominal aortic aneurysms identified by multiplex immunohistochemistry
<p><strong>Background:</strong> Chronic Q fever is a zoonosis caused by the bacterium <em>Coxiella burnetii</em> which can manifest as infection of an abdominal aortic aneurysm (AAA). Antibiotic therapy often fails, resulting in severe morbidity and high mortality. Whereas previous studies have focused on inflammatory processes in blood, the aim of this study was to investigate local inflammation in aortic tissue.</p> <p><strong>Methods:</strong> Multiplex immunohistochemistry was used to investigate local inflammation in Q fever AAAs compared to atherosclerotic AAAs in aorta tissue specimen. Two six-plex panels were used to study both the innate and adaptive immune system.</p> <p><strong>Results: </strong>Q fever AAAs and atherosclerotic AAAs contained similar numbers of CD68<sup>+</sup> macrophages and CD3<sup>+</sup> T cells. However, in Q fever AAAs the number of CD68<sup>+</sup>CD206<sup>+</sup> M2 macrophages was increased, while expression of GM-CSF was decreased compared to atherosclerotic AAAs. Furthermore, Q fever AAAs showed an increase in both the number of CD8<sup>+</sup> cytotoxic T cells and CD3<sup>+</sup>CD8<sup>-</sup>FoxP3<sup>+</sup> regulatory T cells. Lastly, Q fever AAAs did not contain any well-defined granulomas.</p> <p><strong>Conclusions:</strong> These findings demonstrate that despite the presence of pro-inflammatory effector cells, persistent local infection with <em>C. burnetii</em> is associated with an immune suppressed micro environment.</p> <p><strong>Funding:</strong> This work was supported by SCAN consortium: European Research Area - CardioVascualar Diseases (ERA-CVD) grant [JTC2017-044] and TTW-NWO open technology grant [STW-14716].</p>
The translational landscape of SARS-CoV-2 and infected cells reveals suppression of innate immune genes
<p>SARS-CoV-2 utilizes a number of strategies to modulate viral and host mRNA translation. Here, we used ribosome profiling in SARS-CoV-2 infected model cell lines and primary airway cells grown at the air-liquid interface to gain a deeper understanding of the translationally regulated events in response to virus replication. We find that SARS-CoV-2 mRNAs dominate the cellular mRNA pool but are not more efficiently translated than cellular mRNAs. SARS-CoV-2 utilized a highly efficient ribosomal frameshifting strategy despite notable accumulation of ribosomes within the slippery sequence on the frameshifting element. In the highly permissive cell models, although SARS-CoV-2 infection induced the transcriptional upregulation of numerous chemokines, cytokines and interferon stimulated genes, many of these mRNAs were not translated efficiently. Impact of SARS-CoV-2 on host mRNA translation was more subtle in primary cells, with marked transcriptional and translational upregulation of inflammatory and innate immune responses and downregulation of processes involved in ciliated cell function. Together, these data reveal the key role of mRNA translation in SARS-CoV-2 replication and highlight unique mechanisms for therapeutic development. The processed data presented here is derived from the relevant RNA-seq and ribo-seq libraries.</p>
Single Cell Profiling of Human Dura and Meningioma Reveals Cellular Meningeal Landscape and Insights into Meningioma Immune Response
<p>This repository contains the single-cell RNA-seq data described in the publication “Single Cell Profiling of Human Dura and Meningioma Reveals Cellular Meningeal Landscape and Insights into Meningioma Immune Response.” Data is provided as count matrices and Seurat objects.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.