Reconstruction of FACS-partitioned Adaptive Immune Receptor Repertoires from FACS-partitioned B and T Cell Subsets
Zhao, H.; Morgan, A.; Yasuda, M.; Mirebrahim, H.; Schlecht, U.; McNamara, S.; Adachi, R.; Rubelt, F.; Kumar, D.; Utiramerur, S.; Arnaout, R.; Asgharian, H.
Show abstract
Adaptive immune-receptor repertoire sequencing (AIRRseq) is crucial for understanding immune system diversity and its relationship to disease dynamics. Partitioning of total B and T cells into their major subsets with distinct immunological functions - IgM+ vs. class-switched B cells (IgG+ > IgA+) and CD4+ vs. CD8+ T cells, respectively - allows for AIRRseq-based analysis of the unique contributions of each compartment to the overall immune response, a major advantage over traditional bulk sequencing workflows. However, data from these subsets is not directly comparable with the vast majority of publicly available AIRRseq data, which comes from unfractionated B and T cells, an important incompatibility. Here we investigate computational methods for reconstructing complete AIRRseq repertoires from partitioned B and T cell subsets in diverse individuals. Peripheral blood mononuclear cells (PBMCs) were partitioned via positive selection of IgM+ B-cell subsets and CD4+ T cells using immunomagnetic beads; genomic DNA was then extracted and B- and T-cell receptors were sequenced. Four reconstruction methods are introduced and evaluated for concordance with matching unpartitioned repertoires to assess preservation of key repertoire characteristics. Results show that these methods enable accurate estimates of overall immune-repertoire diversity from B- and T-cell subsets in a way that simply pooling the sequence data from sub-repertoires cannot.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Immune cell type signature discovery and random forest classification for analysis of single cell gene expression datasets 93%
- Variation of immune cell responses in humans reveals sex-specific coordinated signaling across cell types 93%
- FlowAtlas.jl: an interactive tool bridging FlowJo with computational tools in Julia 93%
Similar papers in this journal
- An Integrated Approach to the Characterization of Immune Repertoires Using AIMS: An Automated Immune Molecule Separator 93%
- Evaluating the utility of amino acid similarity-aware kmers to represent TCR repertoires for classification 92%
- nf-core/airrflow: an adaptive immune receptor repertoire analysis workflow employing the Immcantation framework 92%
Similar papers in this journal
Similar papers in this journal
- Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2 94%
- Integrative network modeling reveals mechanisms underlying T cell exhaustion 92%
- Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2: toward universal blueprints for vaccine designs 91%
Similar papers in this journal
- TCR meta-clonotypes for biomarker discovery with tcrdist3: identification of public, HLA-restricted SARS-CoV-2 associated TCR features 93%
- Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy 93%
- Characterisation of the immune repertoire of a humanised transgenic mouse through immunophenotyping and high-throughput sequencing 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.