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3 result(s) for "Moghimi, Pejvak"
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sumrep: A Summary Statistic Framework for Immune Receptor Repertoire Comparison and Model Validation
The adaptive immune system generates an incredible diversity of antigen receptors for B and T cells to keep dangerous pathogens at bay. The DNA sequences coding for these receptors arise by a complex recombination process followed by a series of productivity-based filters, as well as affinity maturation for B cells, giving considerable diversity to the circulating pool of receptor sequences. Although these datasets hold considerable promise for medical and public health applications, the complex structure of the resulting adaptive immune receptor repertoire sequencing (AIRR-seq) datasets makes analysis difficult. In this paper we introduce sumrep, an R package that efficiently performs a wide variety of repertoire summaries and comparisons, and show how sumrep can be used to perform model validation. We find that summaries vary in their ability to differentiate between datasets, although many are able to distinguish between covariates such as donor, timepoint, and cell type for BCR and TCR repertoires. We show that deletion and insertion lengths resulting from V(D)J recombination tend to be more discriminative characterizations of a repertoire than summaries that describe the amino acid composition of the CDR3 region. We also find that state-of-the-art generative models excel at recapitulating gene usage and recombination statistics in a given experimental repertoire, but struggle to capture many physiochemical properties of real repertoires.
A human prenatal skin cell atlas reveals immune cell regulation of skin morphogenesis
Human prenatal skin is populated by innate immune cells including macrophages, and whether they act solely in immunity or have additional functions in morphogenesis is unclear. We assembled the first comprehensive multi-omic reference atlas of prenatal human skin (7-16 post-conception weeks), combining single cell and spatial transcriptomic data, to characterise the skin’s microenvironmental cellular organisation. This revealed that crosstalk between non-immune and immune cells underpins formation of hair follicles, has implications for scarless wound healing, and is critical for skin angiogenesis. We benchmarked a skin organoid model, derived from human embryonic stem (ES) and induced pluripotent stem (iPS) cells, against prenatal and adult skin, demonstrating close recapitulation of the epidermal and dermal skin components during hair follicle development. Notably, the skin organoid lacked immune cells and had markedly diminished endothelial cell heterogeneity and quantity. From our in vivo skin cell atlas data, we found that macrophages and macrophage-derived growth factors play a key role in driving endothelial development prenatally. Indeed, vascular network formation was enhanced following transfer of autologous iPS-derived macrophages into both endothelial cell angiogenesis assays and skin organoid cultures. In summary, innate immune cells moonlight as key players in skin morphogenesis beyond their conventional immune roles, a function they achieve via extensive crosstalk with non-immune cells. Finally, we leveraged our human prenatal skin cell atlas to further our understanding of the pathogenesis of genetic hair and skin disorders.
sumrep: a summary statistic framework for immune receptor repertoire comparison and model validation
The adaptive immune system generates an incredible diversity of antigen receptors for B and T cells to keep dangerous pathogens at bay. The DNA sequences coding for these receptors arise by a complex recombination process followed by a series of productivity-based filters, as well as affinity maturation for B cells, giving considerable diversity to the circulating pool of receptor sequences. Although these datasets hold considerable promise for medical and public health applications, the complex structure of the resulting adaptive immune receptor repertoire sequencing (AIRR-seq) datasets makes analysis difficult. In this paper we introduce sumrep, an R package that efficiently performs a wide variety of repertoire summaries and comparisons, and show how sumrep can be used to perform model validation. We find that summaries vary in their ability to differentiate between datasets, although many are able to distinguish between covariates such as donor, timepoint, and cell type for BCR and TCR repertoires. We show that deletion and insertion lengths resulting from V(D)J recombination tend to be more discriminative characterizations of a repertoire than summaries that describe the amino acid composition of the CDR3 region. We also find that state-of-the-art generative models excel at recapitulating gene usage and recombination statistics in a given experimental repertoire, but struggle to capture many physiochemical properties of real repertoires.