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Activated CD4 + T cells bifurcate along the TCF1/BLIMP1 axis. (A) VAC063C single-cell RNAseq workflow: each sample of flow-sorted CD4 + T cells was barcoded using TotalSeq-C oligo-tagged antibodies; samples from all volunteers and time points were pooled (separately for first and third infection); and pooled samples were superloaded onto a 10X Chromium Controller (we aimed to capture 30,000 singlets per pool). GEMs encapsulating a single cell (or doublets) were then generated and from each GEM three libraries were produced: (1) the cell surface <t>barcode,</t> (2) 5′ gene expression, and (3) TCR (after amplification of the V(D)J regions). Libraries were pooled at the specified ratios and sequenced. Finally, we used PCA-based clustering to debarcode all samples and remove doublets (see Materials and methods). (B) Cell Ranger was used to align 5′ gene expression and V(D)J sequencing reads (independently for the first and third infection). Shown is the output of Cell Ranger after removing doublets and performing QC. (C–F) Data from all volunteers and time points was concatenated for UMAP analysis. The expression intensity of markers for memory (C), activation (D), and follicular helper T (T FH ) cell differentiation (E) are shown across the UMAP. The blue line represents the split between naive and memory cells whereas the green line represents the split between memory and activated cells. In F, the expression intensity of the master transcription factors associated with terminal differentiation (BLIMP1) versus the maintenance of stem-like properties (TCF1) are shown. In all cases, each UMAP is equivalent to those shown in (for cross-reference) and square brackets indicate that common protein names have been used. (G) Proposed model of T cell activation during a first-in-life malaria episode. The maintenance of stem-like T cells is essential for long-lived memory; this requires sustained expression of TCF1 to repress BLIMP1 and prevent the terminal differentiation of short-lived effector cells. In A–F, n = 3 for first and third infection.
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Activated CD4 + T cells bifurcate along the TCF1/BLIMP1 axis. (A) VAC063C single-cell RNAseq workflow: each sample of flow-sorted CD4 + T cells was barcoded using TotalSeq-C oligo-tagged antibodies; samples from all volunteers and time points were pooled (separately for first and third infection); and pooled samples were superloaded onto a 10X Chromium Controller (we aimed to capture 30,000 singlets per pool). GEMs encapsulating a single cell (or doublets) were then generated and from each GEM three libraries were produced: (1) the cell surface <t>barcode,</t> (2) 5′ gene expression, and (3) TCR (after amplification of the V(D)J regions). Libraries were pooled at the specified ratios and sequenced. Finally, we used PCA-based clustering to debarcode all samples and remove doublets (see Materials and methods). (B) Cell Ranger was used to align 5′ gene expression and V(D)J sequencing reads (independently for the first and third infection). Shown is the output of Cell Ranger after removing doublets and performing QC. (C–F) Data from all volunteers and time points was concatenated for UMAP analysis. The expression intensity of markers for memory (C), activation (D), and follicular helper T (T FH ) cell differentiation (E) are shown across the UMAP. The blue line represents the split between naive and memory cells whereas the green line represents the split between memory and activated cells. In F, the expression intensity of the master transcription factors associated with terminal differentiation (BLIMP1) versus the maintenance of stem-like properties (TCF1) are shown. In all cases, each UMAP is equivalent to those shown in (for cross-reference) and square brackets indicate that common protein names have been used. (G) Proposed model of T cell activation during a first-in-life malaria episode. The maintenance of stem-like T cells is essential for long-lived memory; this requires sustained expression of TCF1 to repress BLIMP1 and prevent the terminal differentiation of short-lived effector cells. In A–F, n = 3 for first and third infection.
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Activated CD4 + T cells bifurcate along the TCF1/BLIMP1 axis. (A) VAC063C single-cell RNAseq workflow: each sample of flow-sorted CD4 + T cells was barcoded using TotalSeq-C oligo-tagged antibodies; samples from all volunteers and time points were pooled (separately for first and third infection); and pooled samples were superloaded onto a 10X Chromium Controller (we aimed to capture 30,000 singlets per pool). GEMs encapsulating a single cell (or doublets) were then generated and from each GEM three libraries were produced: (1) the cell surface <t>barcode,</t> (2) 5′ gene expression, and (3) TCR (after amplification of the V(D)J regions). Libraries were pooled at the specified ratios and sequenced. Finally, we used PCA-based clustering to debarcode all samples and remove doublets (see Materials and methods). (B) Cell Ranger was used to align 5′ gene expression and V(D)J sequencing reads (independently for the first and third infection). Shown is the output of Cell Ranger after removing doublets and performing QC. (C–F) Data from all volunteers and time points was concatenated for UMAP analysis. The expression intensity of markers for memory (C), activation (D), and follicular helper T (T FH ) cell differentiation (E) are shown across the UMAP. The blue line represents the split between naive and memory cells whereas the green line represents the split between memory and activated cells. In F, the expression intensity of the master transcription factors associated with terminal differentiation (BLIMP1) versus the maintenance of stem-like properties (TCF1) are shown. In all cases, each UMAP is equivalent to those shown in (for cross-reference) and square brackets indicate that common protein names have been used. (G) Proposed model of T cell activation during a first-in-life malaria episode. The maintenance of stem-like T cells is essential for long-lived memory; this requires sustained expression of TCF1 to repress BLIMP1 and prevent the terminal differentiation of short-lived effector cells. In A–F, n = 3 for first and third infection.
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Activated CD4 + T cells bifurcate along the TCF1/BLIMP1 axis. (A) VAC063C single-cell RNAseq workflow: each sample of flow-sorted CD4 + T cells was barcoded using TotalSeq-C oligo-tagged antibodies; samples from all volunteers and time points were pooled (separately for first and third infection); and pooled samples were superloaded onto a 10X Chromium Controller (we aimed to capture 30,000 singlets per pool). GEMs encapsulating a single cell (or doublets) were then generated and from each GEM three libraries were produced: (1) the cell surface <t>barcode,</t> (2) 5′ gene expression, and (3) TCR (after amplification of the V(D)J regions). Libraries were pooled at the specified ratios and sequenced. Finally, we used PCA-based clustering to debarcode all samples and remove doublets (see Materials and methods). (B) Cell Ranger was used to align 5′ gene expression and V(D)J sequencing reads (independently for the first and third infection). Shown is the output of Cell Ranger after removing doublets and performing QC. (C–F) Data from all volunteers and time points was concatenated for UMAP analysis. The expression intensity of markers for memory (C), activation (D), and follicular helper T (T FH ) cell differentiation (E) are shown across the UMAP. The blue line represents the split between naive and memory cells whereas the green line represents the split between memory and activated cells. In F, the expression intensity of the master transcription factors associated with terminal differentiation (BLIMP1) versus the maintenance of stem-like properties (TCF1) are shown. In all cases, each UMAP is equivalent to those shown in (for cross-reference) and square brackets indicate that common protein names have been used. (G) Proposed model of T cell activation during a first-in-life malaria episode. The maintenance of stem-like T cells is essential for long-lived memory; this requires sustained expression of TCF1 to repress BLIMP1 and prevent the terminal differentiation of short-lived effector cells. In A–F, n = 3 for first and third infection.
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Activated CD4 + T cells bifurcate along the TCF1/BLIMP1 axis. (A) VAC063C single-cell RNAseq workflow: each sample of flow-sorted CD4 + T cells was barcoded using TotalSeq-C oligo-tagged antibodies; samples from all volunteers and time points were pooled (separately for first and third infection); and pooled samples were superloaded onto a 10X Chromium Controller (we aimed to capture 30,000 singlets per pool). GEMs encapsulating a single cell (or doublets) were then generated and from each GEM three libraries were produced: (1) the cell surface <t>barcode,</t> (2) 5′ gene expression, and (3) TCR (after amplification of the V(D)J regions). Libraries were pooled at the specified ratios and sequenced. Finally, we used PCA-based clustering to debarcode all samples and remove doublets (see Materials and methods). (B) Cell Ranger was used to align 5′ gene expression and V(D)J sequencing reads (independently for the first and third infection). Shown is the output of Cell Ranger after removing doublets and performing QC. (C–F) Data from all volunteers and time points was concatenated for UMAP analysis. The expression intensity of markers for memory (C), activation (D), and follicular helper T (T FH ) cell differentiation (E) are shown across the UMAP. The blue line represents the split between naive and memory cells whereas the green line represents the split between memory and activated cells. In F, the expression intensity of the master transcription factors associated with terminal differentiation (BLIMP1) versus the maintenance of stem-like properties (TCF1) are shown. In all cases, each UMAP is equivalent to those shown in (for cross-reference) and square brackets indicate that common protein names have been used. (G) Proposed model of T cell activation during a first-in-life malaria episode. The maintenance of stem-like T cells is essential for long-lived memory; this requires sustained expression of TCF1 to repress BLIMP1 and prevent the terminal differentiation of short-lived effector cells. In A–F, n = 3 for first and third infection.
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Activated CD4 + T cells bifurcate along the TCF1/BLIMP1 axis. (A) VAC063C single-cell RNAseq workflow: each sample of flow-sorted CD4 + T cells was barcoded using TotalSeq-C oligo-tagged antibodies; samples from all volunteers and time points were pooled (separately for first and third infection); and pooled samples were superloaded onto a 10X Chromium Controller (we aimed to capture 30,000 singlets per pool). GEMs encapsulating a single cell (or doublets) were then generated and from each GEM three libraries were produced: (1) the cell surface barcode, (2) 5′ gene expression, and (3) TCR (after amplification of the V(D)J regions). Libraries were pooled at the specified ratios and sequenced. Finally, we used PCA-based clustering to debarcode all samples and remove doublets (see Materials and methods). (B) Cell Ranger was used to align 5′ gene expression and V(D)J sequencing reads (independently for the first and third infection). Shown is the output of Cell Ranger after removing doublets and performing QC. (C–F) Data from all volunteers and time points was concatenated for UMAP analysis. The expression intensity of markers for memory (C), activation (D), and follicular helper T (T FH ) cell differentiation (E) are shown across the UMAP. The blue line represents the split between naive and memory cells whereas the green line represents the split between memory and activated cells. In F, the expression intensity of the master transcription factors associated with terminal differentiation (BLIMP1) versus the maintenance of stem-like properties (TCF1) are shown. In all cases, each UMAP is equivalent to those shown in (for cross-reference) and square brackets indicate that common protein names have been used. (G) Proposed model of T cell activation during a first-in-life malaria episode. The maintenance of stem-like T cells is essential for long-lived memory; this requires sustained expression of TCF1 to repress BLIMP1 and prevent the terminal differentiation of short-lived effector cells. In A–F, n = 3 for first and third infection.

Journal: The Journal of Experimental Medicine

Article Title: Plasmodium falciparum infection induces T cell tolerance that is associated with decreased disease severity upon re-infection

doi: 10.1084/jem.20241667

Figure Lengend Snippet: Activated CD4 + T cells bifurcate along the TCF1/BLIMP1 axis. (A) VAC063C single-cell RNAseq workflow: each sample of flow-sorted CD4 + T cells was barcoded using TotalSeq-C oligo-tagged antibodies; samples from all volunteers and time points were pooled (separately for first and third infection); and pooled samples were superloaded onto a 10X Chromium Controller (we aimed to capture 30,000 singlets per pool). GEMs encapsulating a single cell (or doublets) were then generated and from each GEM three libraries were produced: (1) the cell surface barcode, (2) 5′ gene expression, and (3) TCR (after amplification of the V(D)J regions). Libraries were pooled at the specified ratios and sequenced. Finally, we used PCA-based clustering to debarcode all samples and remove doublets (see Materials and methods). (B) Cell Ranger was used to align 5′ gene expression and V(D)J sequencing reads (independently for the first and third infection). Shown is the output of Cell Ranger after removing doublets and performing QC. (C–F) Data from all volunteers and time points was concatenated for UMAP analysis. The expression intensity of markers for memory (C), activation (D), and follicular helper T (T FH ) cell differentiation (E) are shown across the UMAP. The blue line represents the split between naive and memory cells whereas the green line represents the split between memory and activated cells. In F, the expression intensity of the master transcription factors associated with terminal differentiation (BLIMP1) versus the maintenance of stem-like properties (TCF1) are shown. In all cases, each UMAP is equivalent to those shown in (for cross-reference) and square brackets indicate that common protein names have been used. (G) Proposed model of T cell activation during a first-in-life malaria episode. The maintenance of stem-like T cells is essential for long-lived memory; this requires sustained expression of TCF1 to repress BLIMP1 and prevent the terminal differentiation of short-lived effector cells. In A–F, n = 3 for first and third infection.

Article Snippet: Next cells were permeabilized with Maxpar barcode permeabilization buffer (#201057; Fluidigm), and each sample was barcoded using Cell-ID 20-plex palladium barcodes (#201060; Fluidigm).

Techniques: Infection, Generated, Produced, Gene Expression, Amplification, Sequencing, Expressing, Activation Assay, Cell Differentiation