seurat subset multiple conditions

I have similar questions as @attal-kush with regards to reclustering of a subset of an integrated object. The probes were mixed in 1:1 Brilliant Buffer (BD Bioscience) and FACS buffer (PBS with 2% FBS and 2mM EDTA) with 5M of free d-biotin. The commands are largely similar, with a few key differences: Now that the datasets have been integrated, you can follow the previous steps in this vignette identify cell types and cell type-specific responses.Session Info FindAllMarkers and FindMarkers functions were executed with logfc.thresholds set to 0.25 (0.1 for comparing resting Bm cells at month 6 versus month 12) and a min.pct cutoff at 0.1. 3d). a. The most common way is using the objects Idents: Idents (skin) <- "predicted_cell_type" skin_subset <- subset (skin, idents = "0:CD8 T cell") For the code you provided, I believe using quotations around the column name will work: | MergeSeurat(object1 = object1, object2 = object2) | merge(x = object1, y = object2) |. My scenario is very similar to what @attal-kush described. Also, cells previously occurring as cluster outliers from cl7 found their way to the corresponding clusters. P values are provided if significant (p<0.05) between the S and S+ Bm cell subsets. Default is INF. Statistical analysis was performed with GraphPad Prism (version 9.4.1, GraphPad Software, USA) and R (version 4.1.0). Why are these constructs using pre and post-increment undefined behavior? Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article. b) Running FindVariableGenes() and RunPCA() again on the integrated dataset does not seem helpful to me because the limited feature space of 3000 is not changed. ISSN 1529-2916 (online) Improving performance in multiple Time-Range subsetting from xts? Analysis of differentially expressed genes indicated that CD21CD27FcRL5+ B cells were the most distinctive subset and had high expression of TBX21 (encoding T-bet), T-bet-driven genes ZEB2 and ITGAX (encoding CD11c), and TOX (Fig. Dimensionality reduction and clustering analysis of flow cytometry data were performed in R using the CATALYST workflow (CATALYST package, version 1.18.1) (ref. For full details, please read our tutorial. g, Percentages (mean SD) of FcRL4+ Bm cells in paired blood (n=15) and tonsil (n=16) and S+ Bm cells in tonsil samples, separated by SARS-CoV-2-vaccinated (n=8) and recovered patients (n=8). CD21CD27 Bm cells depend on the transcription factor T-bet for their development30, are CD11chi and express inhibitory coreceptors, such as Fc receptor-like protein 5 (FcRL5) (refs. 6d,e). filtered_contig_annotations.csv files obtained from the cellranger multipipeline were used as input for the changeo-10x pipeline. These authors contributed equally: Yves Zurbuchen, Jan Michler. 2.8 years ago. | SetIdent(object = object, cells.use = 1:10, ident.use = "new.idents") | Idents(object = object, cells = 1:10) <- "new.idents" | 124, 10171030 (1966). Nature 604, 141145 (2022). 4h). On what basis are pardoning decisions made by presidents or governors when exercising their pardoning power? The clonality distance threshold was set to 0.20 for the longitudinal analysis of the SARS-CoV-2 Infection Cohort dataset and to 0.05 for the SARS-CoV-2 Tonsil Cohort dataset. g, Frequencies (n=29 pairs; left) and pie charts (right) of indicated S+ Bm cell subsets are provided at indicated timepoints. But reading a few posts and issues here, it's not the way to go and I would like to understand why and to know how to do it properly. then the answer is to run it on the integrated assay). In b, significant differences between groups were determined by constructing a bootstrap delta distribution for each pair of unique values between groups. They were also enriched in gene transcripts involved in interferon (IFN)- and BCR signaling and showed high expression of integrins ITGAX, ITGB2 and ITGB7 (Fig. ## [100] spatstat.utils_3.0-1 tibble_3.1.8 bslib_0.4.2 ## [4] igraph_1.4.1 lazyeval_0.2.2 sp_1.6-0 ## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C In e, two-sided Wilcoxon test was used with Holm multiple comparison correction. 8b,c). Seurat (version 3.1.4) Efficient recall of Omicron-reactive B cell memory after a third dose of SARS-CoV-2 mRNA vaccine. a, Gating strategy for SARS-CoV-2 spike (S)+ and receptor-binding domain (RBD)+ Bm cells. The num_dim parameter of Monocles preprocess_cds() function was set to 20. While functions exist within Seurat to perform DE analysis, the p-values from these analyses are often inflated as each cell is treated as an independent . Many thanks in advance. :) Thank you. Biol. ## [1] cowplot_1.1.1 ggplot2_3.4.1 | levels(x = object@idents) | levels(x = object) | Developed by Paul Hoffman, Satija Lab and Collaborators. DefaultAssay(control_subset) <- "RNA" Briefly, FASTQ files were aligned to the human GRCh38 genome using Cell Rangers cellranger multi pipeline (10x Genomics, v6.1.2) with default settings, which allowed one to process together the paired GEX, ADT and VDJ libraries for each sample batch. Immunity 49, 725739.e6 (2018). It seems that a repeated possibility would be to change the features.to.integrate argument in IntegrateData to all_common_features between the different integrated datasets, however I have a quite big dataset (100.000 cells) and I'm experiencing memory issues: In any case, could this workflow (slightly modified from the one from @attal-kush) be accepted to subcluster from an integrated object? ## [91] RANN_2.6.1 pbapply_1.7-0 future_1.31.0 1 Answer Sorted by: 1 With a little bit of workaround: i) Add a new column to the data slot (only because your original subset () call does so but it can be raw counts or any other data matrix in your Seurat object). Source data are provided with this paper. 33,34) (Fig. i, SHM counts are provided for nave B cells (n=1,607), blood (n=170) and tonsillar SWT+ Bm cells (n=1,128). Below, we demonstrate how to modify the Seurat integration workflow for datasets that have been normalized with the sctransform workflow. Defining antigen-specific plasmablast and memory B cell subsets in human blood after viral infection or vaccination. Thank you! Here we showed that single severe acute respiratory syndrome coronavirus 2-specific Bm cell clones showed plasticity upon antigen rechallenge in previously exposed individuals. (by re-cluster I mean the entire subsetted dataset is treated as an independent body of cells and re-analyzed similar to what you allude to. Most functions now take an assay parameter, but you can set a Default Assay to avoid repetitive statements. Find centralized, trusted content and collaborate around the technologies you use most. 3g,h and Extended Data Fig. Google Scholar. | GetGeneLoadings(object = object, reduction.type = "pca") | Loadings(object = object, reduction = "pca") | Collectively, these observations indicated that individual S+ Bm cell clones could adopt different Bm fates post-vaccination in SARS-CoV-2-recovered individuals. Thanks for contributing an answer to Stack Overflow! | ----- | -------- | 212, 20412056 (2015). 1g and Extended Data Fig. Nevertheless, I have seen that normalized RNA (log norm'd) is very reproducible in a PCR/bulk RNAseq/rnaFISH exp (if your DE gene FC is >1.5x and expressed in atleast 50% of cells). I wonder if anyone has found a definitive answer for this? b, Paired comparison of S+ Bm cell frequencies within B cells (n=34) was performed at preVac and postVac. | RestoreLegend | Restores a legend after removal | Google Scholar. ## Samples in bd were compared using KruskalWallis test with Dunns multiple comparison correction, showing adjusted P values if significant. Chang, L. Y., Li, Y. random.seed = 1, ## [37] survival_3.3-1 zoo_1.8-11 glue_1.6.2 How can I find help page about "%in%"? non zero expression of Cd3e and Cd3g markers in the. Zumaquero, E. et al. BCR-seq showed similar SHM counts in SWT+ Bm cells in blood and tonsils (Fig. e, Representative CD69 histograms in S+ Bm cells of patient CoV-T2 (left) and percentages of CD69+ S+ Bm cells (right) in blood and tonsils. M.E.R. c, Heat map shows selected, significantly differentially expressed genes in indicated S+ Bm cell subsets. Lung-resident memory B cells established after pulmonary influenza infection display distinct transcriptional and phenotypic profiles. Immunol. PubMed I have added them all together and created the VlnPlot to check for the quality of the samples. c. Should FindVariableFeatures be run on the RNA assay, the integrated assay, or the SCT assay? USA 104, 97709775 (2007). 1 Overview of SARS-CoV-2 cohorts analyzed in this study. # One of these Assay objects is called the "default assay", meaning it's used for all analyses and visualization. Niessl, J. et al. All samples were analyzed by flow cytometry and paired blood and tonsil samples from four patients also by scRNA-seq. Internet Explorer). The FCRL4hiENTPD1hiTNFRSF13Bhi cluster (cluster 6) probably represented the FcRL4+ B cell subset, and contained very few SWT+ Bm cells (Fig. The transient occurrence of vaccine-specific CD21CD27 Bm cells has been described during responses to the influenza vaccine12,20, with one study reporting this Bm cell subset in de novo rather than recall responses20. that a certain variable was either 1, 2 or 3. d, Venn diagram displays clonal overlap of SARS-CoV-2-specific clones at months 6 and 12 post-infection. ## [127] MASS_7.3-56 rprojroot_2.0.3 withr_2.5.0 The alternative would be to subset() the population of interest and run the complete preprocessing including integration only on those cells again. 59). *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001. a, Sorting strategy for SARS-CoV-2 S+ Bm cells and S B cells, gated on CD19+ non-PB, for scRNA-seq is provided. Human T-bet governs the generation of a distinct subset of CD11chighCD21low B cells. 6, eabh0891 (2021). g, UMAPs represent Monocle 3 analysis of all Bm cells (left) and S+ Bm cells (right). Is short-circuiting logical operators mandated? 2e), which correlated with an improved binding breadth, as measured by variant-binding ability of SWT+ Bm cells (Fig. Peer reviewer reports are available. contributed to patient recruitment and clinical management. Med. Imprinted SARS-CoV-2-specific memory lymphocytes define hybrid immunity. Gene set variation analysis with the package gsva (v1.42.0) was used to estimate gene set enrichments for more than two groups61. 565), Improving the copy in the close modal and post notices - 2023 edition, New blog post from our CEO Prashanth: Community is the future of AI. j, WNNUMAP was derived as in f and colored by tissue origin. The joint analysis of two or more single-cell datasets poses unique challenges. Note that @timoast from the Seurat team recommended otherwise, although I never seen an explanation why would this not best way to go. BCR diversity was slightly reduced in S+ CD21CD27FcRL5+ compared with S+ CD21+ resting Bm cells (Extended Data Fig. Article Numbers indicate percentages of parent population. 6, eabg6916 (2021). P values are shown if significant (p<0.05). 5c). I.E.A. | RotatedAxis | Rotates x-axis labels |. Is it necessary to run FindVariableFeatures on the RNA assay of the subset and get new variables to use in PCA in order to properly cluster the subset? | SetIdent(object = object, ident.use = "new.idents") | Idents(object = object) <- "new.idents" | | FilterCells(object = object, subset.names = "name", low.threshold = low, high.threshold = high) | subset(x = object, subset = name > low & name < high) | 15, 149159 (2015). Tonsils were processed according to established protocols47,53. Because we are confident in having identified common cell types across condition, we can ask what genes change in different conditions for cells of the same type. Takes either a list of cells to use as a subset, or a parameter (for example, a gene), to subset on. Immunity 53, 11361150 (2020). ## [10] qqconf_1.3.1 TH.data_1.1-1 digest_0.6.31 g, Heat map represents V heavy (VH) gene usage, in RBD+ and RBD Bm cells in scRNA-seq dataset from months 6 and 12. isn't the whole point of integration to remove batch effects? Expression of Blimp-1, T-bet, FcRL5 and CD71 were increased on S+ Bm cells during acute infection compared with months 6 and 12 post-infection (Fig. For scRNA-seq data, distribution was assumed to be normal, but this was not formally tested. Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article. Warnatz, K. et al. 4h). (default), then this list will be computed based on the next three J.M. 3 Identification of SARS-CoV-2 S, Extended Data Fig. | ----------- | ----------- | Annu. VH and V light (VL) genes are indicated on top of dendrograms. Unless a gene is not expressed (n-reads) at 1/p* try to forget about it just like a bad day (p* being the relative mean gene expression taking into account cDNA library construction efficiency, which in the case of 10x is 15%, or 1/p* = 1/0.15 7 reads/cell/gene). Abela, I. Levine, J. H. et al. Making statements based on opinion; back them up with references or personal experience. ), Innovation grant of University Hospital Zurich (to O.B. designed and performed flow cytometry and scRNA-seq experiments, and analyzed and interpreted data. Med. Hopp, C. S. et al. Durable SARS-CoV-2 B cell immunity after mild or severe disease. 5 Flow cytometry analysis of tonsillar and circulating SARS-CoV-2-specific B. We recruited 11 healthy controls (Extended Data Fig. Now, I have a Seurat object with 3 assays: RNA, SCT, and Integrated. Samples in cf were compared using KruskalWallis test with Dunns multiple comparison, showing adjusted P values. Lines connect samples of same individual. Science 371, eabf4063 (2021). The beginning of pseudotime was manually set inside the partition with mostly unswitched B cells. Lines connect samples of same individual. c, UMAP as in a was colored by normalized expression of indicated markers. We found that S+ CD21CD27 Bm cells showed signs of increased antigen processing and presentation; how much this might translate into truly increased capacity of antigen presentation is unclear43. Cheers, all look forward to learning more on this when the devs respond. a) My approach would be to just run FindClusters() with a higher resolution on the whole dataset until the desired subclustering is reached. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. Wang, Z. et al. d, Violin plots comparing frequencies of CD21CD27+, CD21CD27, CD21+CD27+ and CD21+CD27 S+ Bm cell subsets are separated by timepoints post-infection and mild (acute infection, n=15; month 6, n=33; month 12, n=10) and severe COVID-19 (acute infection, n=8; month 6, n=19; month 12, n=6). After sorting, cell suspensions were pelleted at 400g for 10min at 4C, resuspended and loaded into the Chromium Chip following the manufacturers instructions. The B cell response to different pathogens uses tailored effector mechanisms and results in functionally specialized memory B (Bm) cell subsets, including CD21+ resting, CD21CD27+ activated and CD21CD27 Bm cells. Y.Z. g, Stacked bar graphs show contribution of total Bm cell subsets to Monocle clusters. Heat maps were generated using the ComplexHeatmap package (v2.13.1) or pheatmap package (v1.0.12) (ref. These results suggest that CD21CD27 Bm cells partake in the normal immune response to pathogens37. ), Filling the Gap Program of UZH (to M.E.R. If NULL 7, eabf5314 (2022). Clonal diversity between Bm cell subsets was investigated using the alphaDiversity function of Immcantations package Alakazam (v1.2.0) (ref. d. Should ScaleData be run on the subset prior to PCA even though the subset comes from an integrated object prepped from SCT? 5a,b and Extended Data Fig. analyzed scRNA-seq data. J. Exp. First, we focused on samples from nonvaccinated individuals at acute infection (n=59, day 14 on average after symptom onset), month 6 (n=61, day 202 after symptom onset) and month 12 (n=17, day 374) (Fig. ## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so.3 a, Donut plots of BCR sequences of S+ Bm cells in three representative patients preVac and postVac. VASPKIT and SeeK-path recommend different paths. Sample assignment of cells was done using TotalSeq-based cell hashing and Seurats HTODemux() function. @vertesy just came here to chime in after seeing your comment mate, so I tried what you are suggesting, and I see no marked difference, in fact, I don't have the data to show rn because I've a lot on my plate currently, but subset>integrate>re-cluster is more laborious and less useful than integrate>subset>re-cluster. Already on GitHub? Extended Data Fig. 7d). Cells with LIBRA scores >0 for the respective antigens were defined as antigen-specific, and in the SARS-CoV-2 infection, cohort cells were considered S+ if any of the antigens used for baiting (SWT, Sbeta, Sdelta, RBD) were defined as specific. Standard edgeR workflow was used to create a linear model for the count data and to conduct statistical tests for differential segment usage between Bm cell subsets. c, Frequency of S+ Bm cells in total B cells was measured by flow cytometry at acute infection (n=59) and months 6 (n=61) and 12 post-infection (n=17). In d, frequencies were compared using a two-tailed, two-proportions z-test with a Bonferroni-based multiple testing correction. The cohort size was based on sample availability. Prolonged evolution of the human B cell response to SARS-CoV-2 infection. Hello, Naturally enhanced neutralizing breadth against SARS-CoV-2 one year after infection. and reading this issue I only got more confused. AverageExpression: Averaged feature expression by identity class Hugo. T-bet+ B cells are induced by human viral infections and dominate the HIV gp140 response. Robbiani, D. F. et al. a, Heatmap compares V heavy (VH; left) and VL (right) gene usage in indicated S+ Bm cell subsets and S Bm cells (non-binders) from scRNA-seq data of SARS-CoV-2-infected patients at months 6 and 12 post-infection. Of these individuals, 35 received one or two doses of SARS-CoV-2 mRNA vaccination between month 6 and month 12, and three subjects were vaccinated between acute infection and month 6 (Supplementary Table 1 and Extended Data Fig. d, Exemplary dendrograms (IgPhyML B cell trees) display different persistent Bm cell clones at months 6 (triangles) and 12 (dots) post-infection. In other words, is this workflow valid: ## [52] metap_1.8 viridisLite_0.4.1 xtable_1.8-4 56), with k set to 20, the following B cell markers were used: CD11c, CD19, CD20, CD21, CD24, CD27, CD38, CD71, CD80, CXCR5, BAFF-R, FcRL5, IgA, IgD, IgG, IgM, Blimp1, IRF8, Ki67 and Tbet. Thank you. between condition A cluster 1 vs. condition B cluster 1 cells). Poon, M. M. L. et al. control_subset <- RunPCA(control_subset, npcs = 30, verbose = FALSE) to f, Waffle plots represent SWT+ Bm cells binding Sbeta and Sdelta in nonvaccinated individuals (n=9 at month 6 and n=3 at month 12 post-infection). 6c). Rev. Nature 602, 148155 (2021). All the best, To extend our analyses to SARS-CoV-2-specific Bm cells in the peripheral lymphoid organs, we analyzed paired tonsil and blood samples from a cohort of 16 patients (9 females and 7 males) undergoing tonsillectomy who were exposed to SARS-CoV-2 by infection, vaccination or both. As you can see, many of the same genes are upregulated in both of these cell types and likely represent a conserved interferon response pathway. I want to subset a specific cell type (cluster) and examine subtypes in this cell type. We observed a strong increase in the frequency of S+ and RBD+ Bm cells in SARS-CoV-2-infected individuals at months 6 (median 0.14% and 0.033%, respectively) and 12 post-infection (median 0.068% and 0.02%) compared with acute infection (median 0.016% and 0.0023%) (Fig. 13, 446 (2022). d, Clonality of S+ Bm cells was analyzed preVac and postVac in scRNA-seq dataset. Transl. the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Distinct effector B cells induced by unregulated Toll-like receptor 7 contribute to pathogenic responses in systemic lupus erythematosus. I then change DefaultAssay to RNA, run SCTransform() again setting the do.scale = TRUE, and do.center = TRUE. During acute infection S+ CD21CD27+ Bm cells and CD21CD27 Bm cells represented on average 48.1% and 16.4% of total S+ Bm cells, respectively, and they strongly declined at month 6 (6.3% and 5.3%) and month 12 (3.7% and 6.6%) post-infection (Fig. The antigen presenting potential of CD21low B Cells. So I have a couple of questions regarding my workflow: For downstream DE analysis, the scale.data slot in the SCT assay has disappeared after integration. and O.B. Tracking of individual B cell clones by B cell receptor sequencing revealed that previously fated Bm cell clones could redifferentiate upon antigen rechallenge into other Bm cell subsets, including CD21CD27 Bm cells, demonstrating that single Bm cell clones can adopt functionally different trajectories. It did always just select values that matched the first of the criteria, here 1. Creates a Seurat object containing only a subset of the cells in the original object. P values in e and g are shown if significant. Also, please provide a reproducible example data for testing, dput (myData). Honestly now I'm very stringent on what my definition of a DE is because minor gene fluctuations in scRNAseq data are very unreliable and reside within the realm of false-positive dropouts. I just do not want to do manual subsetting on 10 genes, then manually getting @data matrix from each subset, and recreating seurat object afterwards. Are these the correct steps to follow? control_subset <- RunPCA(control_subset, npcs = 30, verbose = FALSE) By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Colors indicate frequency within RBD+ and RBD Bm cells. 351 2 15. Samples in d were compared using KruskalWallis test with Dunns multiple comparison correction, showing adjusted P values if significant. Final libraries were quantified using a Qubit Fluorometer, pooled at ratios of 5:1:1 or 10:1:1 (GEX:VDJ:ADT) and sequenced on a NovaSeq 6000 system. Different batches were aligned using Batchelor (v.1.10.0) (ref. ## [61] ellipsis_0.3.2 ica_1.0-3 farver_2.1.1 2f). We would all appreciate it if @timoast or others from the @satijalab can chime in. Immunol. Thank you @satijalab for this amazing tool and the amazing tutorials !!!! But I especially don't get why this one did not work: 3c). Google Scholar. object, Results were filtered for gene sets that were significantly enriched with adjusted P<0.05. PhenoGraph clustering identified an IgG+CD21CD27 cluster (cluster 2), which was TbethiCD11c+FcRL5+, and CD21CD27+ clusters characterized by high expression of CD71, Blimp-1 and Ki-67 (clusters 1, 7 and 8) (Extended Data Fig. Sign up for the Nature Briefing newsletter what matters in science, free to your inbox daily. k, Venn diagram shows clonal overlap of SWT+ and SWT Bm cells in tonsils and blood from scRNA-seq dataset. Taken together, resting antigen-specific Bm cells were found in the tonsils after SARS-CoV-2 exposure, and they carried signs of tissue adaptation and clonal connection to their circulating counterparts. Bhattacharya, D. Instructing durable humoral immunity for COVID-19 and other vaccinable diseases. Lines connect paired samples. For example, to only cluster cells using a single sample group, control, we could run the following: . We also introduce simple functions for common tasks, like subsetting and merging, that mirror standard R functions. Lines connect samples of same individual. 6b), whereas at month 12 post-infection (post-vaccination) 32% of persistent Bm clones showed a CD21CD27+CD71+ and 28% a CD21CD27FcRL5+ Bm cell phenotype. The text was updated successfully, but these errors were encountered: @attal-kush I hope its okay to piggyback of your question. Conversely, the frequency of S+ CD21CD27 Bm cells rose quickly and remained stable over 150days post-vaccination, accounting for about 20% of S+ Bm cells (Fig. However, when I try to do any of the following: I am at loss for how to perform conditional matching with the meta_data variable. That would be great if someone can confirm or deny :). 9d). How to perform subclustering and DE analysis on a subset of an integrated object, Supervised clustering on a subset of integrated object (best practices?). I know that I can do subsetting on just one gene in Seurat: However, I want to subset on multiple genes. Immunol. subset.name = NULL, Article That enables to change the feature space. sessionInfo()## R version 4.2.0 (2022-04-22) ## [7] splines_4.2.0 listenv_0.9.0 scattermore_0.8 2019 as referred to by @tilofreiwald. Multifactorial seroprofiling dissects the contribution of pre-existing human coronaviruses responses to SARS-CoV-2 immunity. subset.name = NULL, I wanted to base an analysis on data that that was matching one of a few criteria, e.g. B cells that differentiate in the GC undergo affinity maturation through somatic hypermutation (SHM) of the B cell receptor (BCR) following which B cells can become long-lived plasma cells or Bm cells4,5,6. Ellebedy, A. H. et al. How to create a virtual ISO file from /dev/sr0, enjoy another stunning sunset 'over' a glass of assyrtiko. Proc. Bm cells are colored by cluster (f, left), tissue origin (f, right) or SWT binding (g). dg, Stacked bar graphs display tissue (d) and isotype distribution (e) in Bm cell clusters, and isotype (f) and cluster distribution (g) in SWT+ Bm cells in tonsils and blood. The ideal workflow is not clear to me and perusing the vignettes and past issues did not clarify it fully. In g, two-sided Wilcoxon test was used with Holm multiple comparison correction. Branch lengths represent mutation numbers per site between each node. Box plots show median, box limits, and interquartile ranges (IQR), with whiskers representing 1.5x IQR and outliers. Did the Golden Gate Bridge 'flatten' under the weight of 300,000 people in 1987? ), Swiss Academy of Medical Sciences (SAMW) fellowships (#323530-191230 to Y.Z. T-bet+ B cells have a protective role in mouse models of acute and chronic viral infections38,42. With Seurat, you can easily switch between different assays at the single cell level (such as ADT counts from CITE-seq, or integrated/batch-corrected data). Powered by the https://doi.org/10.1038/s41590-023-01497-y, DOI: https://doi.org/10.1038/s41590-023-01497-y. As cell identity is only available after intergration and clustering? accept.value = NULL, 7ac). SARS-CoV-2 spike-specific memory B cells express higher levels of T-bet and FcRL5 after non-severe COVID-19 as compared to severe disease. Johnson, J. L. et al. Increased memory B cell potency and breadth after a SARS-CoV-2 mRNA boost, BNT162b2 vaccine induces divergent B cell responses to SARS-CoV-2 S1 and S2, Systematic comparison of respiratory syncytial virus-induced memory B cell responses in two anatomical compartments, Single-cell epigenomic landscape of peripheral immune cells reveals establishment of trained immunity in individuals convalescing from COVID-19, The germinal centre B cell response to SARS-CoV-2, Anti-SARS-CoV-2 receptor-binding domain antibody evolution after mRNA vaccination, Human CD8+ T cell cross-reactivity across influenza A, B and C viruses, SARS-CoV-2 antigen exposure history shapes phenotypes and specificity of memory CD8+ T cells, Signature of long-lived memory CD8+ T cells in acute SARS-CoV-2 infection, https://github.com/Moors-Code/MBC_Plasticity_Moor_Boyman_Collaboration. # To see all keys for all objects, use the Key function. Clustering was performed using the Louvain algorithm and a resolution of 0.4. Several of these differences, such as T-bet, and CD11c, were confirmed at the protein level (Fig. Seurat has a vast, ggplot2-based plotting library. b, Distribution of S+ Bm cell subsets is provided at month 6 preVac, month 12 nonVac and month 12 postVac. In the scRNA-seq dataset, CD21+CD27+ resting Bm cells were the main S+ Bm cell subset at months 6 and 12 post-infection in nonvaccinated individuals, whereas CD21CD27+CD71+ activated and CD21CD27FcRL5+ Bm cells became predominant post-vaccination at month 12 post-infection (Fig. Pseudotime-based trajectory analysis using Monocle 3 in our scRNA-seq dataset (Extended Data Fig. Cutting edge: B cellintrinsic T-bet expression is required to control chronic viral infection. | object@cell.names | colnames(x = object) | Cell 179, 16361646.e15 (2019). For the SARS-CoV-2 Tonsil Cohort, we used a cutoff of 7.5% detected mitochondrial genes. Google Scholar. Fourteen cycles (in one case 17) of initial cDNA amplification were used for all sample batches, and single-cell sequencing libraries for whole-transcriptome analysis (GEX), BCR profiling (VDJ) and TotalSeq (BioLegend) barcode detection (ADT) were generated.

Obituaries Malaga, Spain, How To Remove Salary From Indeed, Yolo County Housing Authority Payment Standards, Articles S