Journal: bioRxiv

Article Title: Temporally overlapping mechanisms diversify clonal B cell responses in vivo

doi: 10.1101/2024.12.17.628863

Figure Lengend Snippet: (A) Experimental plan to study B cell differentiation in Pc AS-infected mice, with or without anti-malarial drug treatment, sorting CD19 + B220 int-hi IgD lo splenic B cells at various timepoints p.i. to perform droplet-based, paired single cell RNA and BCR sequencing. (B) Annotated combined UMAP of all mice, treatments and timepoints after high-dimensional reduction and clustering (left), with quantitation (right) of the proportion of selected, annotated B cells over the course of Pc AS infection (no drug treatment). (C) Sub-clustering of the GC cluster identifies distinct DZp, DZd, LZ/DZ and LZ GC B cell clusters as indicated in the dot plot of canonical markers and gene signatures of known GC B cell subsets. Also shown is quantitation of different GC B cell populations over time. RCTD spatial deconvolution of GC B cell populations on a day 30, Plasmodium infected spleen using Slide-seqV2 spatial transcriptomics (right). (D) Median Aicda gene expression in GC B cell subsets and naive B cells as negative control. (E) Median Aicda expression shown overtime, with or without anti-malarial treatment in DZd and DZp GC B cells. (F) Somatic hypermutation analysis of GC B cell BCRs and isotype usage overtime, split by treatment, showing mutation rates for both treatments. Median number of mutations for each treatment and timepoint indicated in white. Data in B-C are shown as mean ± S.D. and analysed by one-way ANOVA with Tukey’s multiple comparisons test of n = 3 biological replicates. * p < 0.05.

Article Snippet: Spatial transcriptomics was performed using Slide-seqV2 at the Broad Institute of Harvard and MIT, as described elsewhere .

Techniques: Cell Differentiation, Infection, Sequencing, Quantitation Assay, Expressing, Negative Control, Mutagenesis

Journal: bioRxiv

Article Title: Temporally overlapping mechanisms diversify clonal B cell responses in vivo

doi: 10.1101/2024.12.17.628863

Figure Lengend Snippet: (A) scVI integration of our day 10-42 B cell dataset with publicly available scRNAseq bone marrow data combined and split by each dataset, with arrow indicating inferred trajectory of Lee et al., 2021 dataset. (B) Annotated B cell scVI integrated UMAP (experiment 1 and experiment 2) of specific precursor B cell subsets during extramedullary B lymphopoiesis: pro-, cycling pro-, pre- and immature B cells split overtime, with or without anti-malarial drug treatment and quantified per replicate mouse. (C) Il7r gene expression highlighted on proB and preB cells. IL7R surface marker used to identify precursor B cells shown by representative flow cytometry panel of B cells gated on CD45.2 - (intravenous label negative, IV - ), CD19 + B220 + CD138 - CD38 + Fas - IgD - CD93 + for immature B cells (IgM + IL7R - ), pro-B cells (IgM - IL7R + , CD43 hi CD24 int ) and pre-B cells (IgM - IL7R + , CD43 int CD24 hi ) in uninfected mice and at day 21 post- Pc AS infection, with quantitation of splenic precursor B cells at 0, 14 and 21 days p.i. (D) RCTD spatial deconvolution of immature B cell populations from Plasmodium infected spleen at day 30 p.i. using Slide-seqV2 spatial transcriptomics, showing spearman’s correlation analysis of cell co-localisations from a scRNAseq reference with location of selected populations including immature B cells (green) plotted on the array. (E) Schematic of different B cell dynamics including extramedullary B lymphopoiesis (EMBL) in our Plasmodium infection system. Lines in panel B connect the mean values at each timepoint and analysed by Welch’s t -test and panel C by one-way ANOVA with multiple comparisons test of n = 10-20 pooled from 2 independent experiments. Data in panel C are the mean value. * p < 0.05, *** p < 0.001, **** p < 0.0001. ns, not significant.

Article Snippet: Spatial transcriptomics was performed using Slide-seqV2 at the Broad Institute of Harvard and MIT, as described elsewhere .

Techniques: Expressing, Marker, Flow Cytometry, Infection, Quantitation Assay

Journal: bioRxiv

Article Title: Temporally overlapping mechanisms diversify clonal B cell responses in vivo

doi: 10.1101/2024.12.17.628863

Figure Lengend Snippet: RCTD spatial deconvolution of immature B cell populations (highlighted in purple) on spatial transcriptomic arrays using Slide-seqV2 and analysed using spearman’s correlation analysis as in . These arrays are replicates for data shown in , and combined they comprise two arrays per spleen from two infected mice.

Article Snippet: Spatial transcriptomics was performed using Slide-seqV2 at the Broad Institute of Harvard and MIT, as described elsewhere .

Techniques: Infection