Data from: Clone tracking through repeated malaria reveals high-fidelity CD4+ memory responses
Data files
Aug 27, 2025 version files 7.57 GB
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multiome_chromvar.rds
2.01 GB
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README.md
5.01 KB
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rna_tcr_malaria_specific.rds
4.70 GB
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rna_tcr_MalNaive_ref_mapped_use.rds
600.39 MB
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rna_tcr_tr1.rds
260.37 MB
Abstract
Few studies have assessed the clonality and functional fidelity of human CD4+ T cells responding to repeated infections in vivo. We utilized broad, longitudinal single-cell RNA and TCR tracking to study the functional stability and memory potential of thousands of CD4+ T cell clonotypes through repeated Plasmodium falciparum (Pf) infections over the course of hundreds of days. Strikingly, nearly all memory CD4+ T cell clonotypes displayed a strong preference for one of seven different subsets—Tcm, Th1, cytotoxic Th1, Th2, Th17, Treg, and Tr1. This phenomenon, which we call “clonal fidelity,” was influenced by clonal expansion, demonstrating an in vivo relationship between T cell polarization and proliferation. Using clone tracking, we characterized subset-specific trajectories of CD4+ T cell activation and identified clonotypes with specific reactivity to Plasmodium falciparum (Pf) blood-stage antigens. Tr1 cells, a peripherally-induced regulatory subset distinct from FOXP3+ Tregs, accounted for nearly 90% of Pf-specific CD4+ T cells. Tracking T cell clones longitudinally in humans, we observed malaria-induced clonal expansion of Tr1 effectors, long-term persistence of Tr1 memory cells, and high-fidelity recall responses following reinfection. Ultimately, this work establishes clonal fidelity as a natural phenomenon and demonstrates the stable, long-term memory potential of the previously enigmatic Tr1 cell.
https://doi.org/10.5061/dryad.59zw3r2jw
Description of the data and file structure
These processed data files are Seurat objects that were generated from raw data available from NCBI (BioProject PRJNA1129481).
The code used to generate these files is available on GitHub (jason-nideffer/clone-tracking-in-malaria).
These files can be used (in conjunction with code available on GitHub) to reproduce the figures in the manuscript titled: "Clone tracking through repeated malaria reveals high-fidelity CD4+ memory responses."
Files and variables
File: rna_tcr_malaria_specific.rds
Description: seurat object containing single memory CD4+ T cells analyzed by RNA/TCRseq. This object is the product of a full data processing pipeline (GitHub: jason-nideffer/clone-tracking-in-malaria; Steps 1-11). The seurat object includes metadata on a per-cell basis. These metadata provide TCR/clonal information, annotations, and describe which sample a cell came from.
Metadata: Metadata variables in this object are largely the same as metadata variables in rna_tcr_malaria_specific.rds.
File: rna_tcr_tr1.rds
Description: seurat object containing only Tr1 cells. It contains a subset of the cells in 'rna_tcr_malaria_specific.rds' that were reclustered.
Metadata: The most relevant variables included in the metadata of this seurat object are as described below:
cohortid- the id of the study participant from which the cell was derivedCTaa- the amino acid sequences of the alpha and beta chains of the TCRsample- the sample from which the cell was derivedcell_type- the annotation of a cell based on its effector functionstimepoint- the timepoint from which the cell was derived. The number simply indicated chronology relative to other sample timepoints of the same study participant.seurat_clusters- the cluster annotation assigned using the Seurat function FindClusters.activation_status- the annotation of a cell based on its activation status (i.e., whether it displays a transcriptional signature of recent TCR activation, interferon stimulation, proliferation, or resting).clonotype_count_per_sample- the number of cells that are from the same sample and that have the sameCTaaas that cell.clonotype.identity_count_per_sample- the number of cells that are from the same sample and that have the sameCTaaandcell_typeas that cell.clonotype_freq_per_sample- the frequency of cells within the sample that have the sameCTaaas that cell.clonotype.identity_freq_per_sample- the frequency of cells within the sample that have the sameCTaaandcell_typeas that cell.clone_family- the clone family to which the cell belongs. In this context, clone family refers to the bias that a clone has for a particular phenotype (cell_type). 1 = Th2; 2 = Tcm; 3 = Th1; 4 = Th17; 5 = Cytotoxic Th1; 6 = Treg; 7 = Tr1.malaria_specific- whether or not the cell encodes a TCR that recognized Plasmodium falciparum blood stage antigens.
File: rna_tcr_MalNaive_ref_mapped_use.rds
Description: seurat object containing single memory CD4+ T cells from 2 malaria-naive adults analyzed by RNA/TCRseq.
Metadata: Metadata variables in this object are largely the same as metadata variables in rna_tcr_malaria_specific.rds.
File: multiome_chromvar.rds
Description: seurat object containing single memory CD4+ T cells analyzed by multiome sequencing. This object was annotated by mapping to 'rna_tcr_malaria_specific.rds' as a reference.
Metadata: Metadata variables in this object represent standard variables from Seurat/Signac processing with some important exceptions:
sample- the sample from which the cell was derived.cohortid- the id of the study participant from which the cell was derivedtimepoint- the timepoint from which the cell was derived. The number does not necessarily indicate chronology.predicted.cell_type- the cell type annotation transferred after mapping this multiome dataset to scRNAseq data. This annotation does not represent the final cell type annotation used for downstream analysis.
Code/software
In addition to Seurat, phenoclone (GitHub: jason-nideffer/phenoclone) is required to reproduce analyses using these data.
Access information
Other publicly accessible locations of the data:
- NCBI (BioProject PRJNA1129481)
Data was derived from the following sources:
- NCBI (BioProject PRJNA1129481)
- GitHub: jason-nideffer/clone-tracking-in-malaria
Questions?
For any questions about these data, please contact Prasanna Jagannathan (prasj@stanford.edu).
Human subjects data
We have received explicit consent from all study participants to publish de-identified metadata and data derived from biological samples.
These processed data files are seurat objects that were generated from raw data available from NCBI (BioProject PRJNA1129481).
The code used to generate these files is available on GitHub (jason-nideffer/clone-tracking-in-malaria).
These files can be used (in conjunction with code available on GitHub) to reproduce the figures in the manuscript titled: "Clone tracking through repeated malaria reveals high-fidelity CD4+ memory responses."
