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Parish, I. A.

Publications and source records attributed to Parish, I. A..

5 recordsLinked to original sources

ClustoCell reveals cell states and their markers from single-cell transcriptomes

Accurate identification of cell types and states is essential for reliable single-cell RNA-sequencing analyses, yet current methods remain sensitive to continuous biological states, data preprocessing choices, and reference selection. Here we present ClustoCell, a reference-free method that resolves cell identity using within-cell transcriptional architecture. By stratifying gene expression of each cell into high and medium tiers, ClustoCell constructs cell-cell similarity graphs that prioritize intrinsic expression structure over global variance. Across 450 datasets spanning over 24 million cells, ClustoCell recovered expert annotations with high concordance (92%). Benchmarked against state-of-the-art methods, ClustoCell identifies more stable and coherent cell types and states, avoids excessive partitioning of closely related cells, and improves the identification of cell type-specific markers. From transcriptional structure alone, ClustoCell resolves rare and transitional cell states, distinguishes malignant from non-malignant cells, and refines expert cell annotations. Applied to immunotherapy datasets, ClustoCell uncovered coordinated pre-treatment immune circuits linking T cell states to PD-1 responsiveness in a tumour-type-specific manner. ClustoCell provides an interpretable and scalable foundation for single-cell analysis and translational profiling.

bioinformatics↗

FixNCut: Single-cell genomics through reversible tissue fixation and dissociation

The use of single-cell technologies for clinical applications requires disconnecting sampling from downstream processing steps. Early sample preservation can further increase robustness and reproducibility by avoiding artifacts introduced during specimen handling. We present FixNCut, a methodology for the reversible fixation of tissue followed by dissociation that overcomes current limitations. We applied FixNCut to human and mouse tissues to demonstrate the preservation of RNA integrity, sequencing library complexity, and cellular composition, while diminishing stress-related artifacts. Besides single-cell RNA sequencing, FixNCut is compatible with multiple single-cell and spatial technologies, making it a versatile tool for robust and flexible study designs.

bioinformatics↗

Type I interferon dynamics determines memory B cell epigenetic identity in chronic viral infection

Memory B cells are key providers of long-lived immunity against infectious disease, yet in chronic viral infection they do not produce effective protection. How chronic viral infection disrupts memory B cell development, and whether such changes are reversible, remains unknown. Here, we uncover type-I interferon (IFN-I) dynamics as a key determinant in shaping chronic memory B cell development. Through single-cell (sc)ATAC-sequencing and scRNA-sequencing, we identified a unique memory subset enriched for IFN-stimulated genes (ISGs) during chronic lymphocytic choriomeningitis virus infection. Blockade of IFNAR-1 early in infection transformed the chromatin landscape of chronic memory B cells, decreasing accessibility at ISG-inducing transcription factor binding motifs and inducing a phenotypic change in the dominating memory B cell subset. However, timing was critical, with memory B cells resistant to intervention after 4 weeks post-infection. Together, our research identifies a key mechanism to instruct memory B cell identity during viral infection. One Sentence Summary: IFN dynamics in chronic versus acute viral infection determines memory B cell development.

immunology↗

Uncontrolled CD21low age-associated and B1 B cell accumulation caused by failure of an EGR2/3 tolerance checkpoint

CD21low age-associated or atypical memory B cells, enriched for autoantibodies and poised for plasma cell differentiation, accumulate in large numbers in chronic infections, autoimmune disease and immunodeficiency, posing the question of what checkpoints normally oppose their excessive accumulation. Here, we reveal a critical role for the calcium-NFAT-regulated transcription factors EGR2 and EGR3. In the absence of EGR2 and EGR3 within B cells, CD21low and B1 B cells accumulate and circulate in young mice in numbers 10-20 times greater than normal, over-express a large set of EGR2 ChIP-seq target genes including known drivers of plasma cell differentiation and under-express drivers of follicular germinal centers. Most follicular B cells constitutively express Egr2 proportionally to surface IgM down-regulation by self-antigens, and EGR2/3 deficiency abolishes this characteristic anergy response. These results define a key transcriptional checkpoint repressing CD21low B cell formation and inform how NFATC1 or EGR2 mutations promote B1 cell-derived chronic lymphocytic leukemias.

immunology↗

Efficient CRISPR/Cas9 gene ablation in uncultured naive mouse T cells for in vivo studies

CRISPR/Cas9 technologies have revolutionised our understanding of gene function in complex biological settings, including T cell immunology. Current CRISPR-mediated gene deletion strategies in T cells require in vitro stimulation or culture that can both preclude studies of gene function within unmanipulated naive T cells and can alter subsequent differentiation. Here we demonstrate highly efficient gene deletion within uncultured primary naive murine CD8+ T cells by electroporation of recombinant Cas9/sgRNA ribonucleoprotein immediately prior to in vivo adoptive transfer. Using this approach, we generated single and double gene knock-out cells within multiple mouse infection models. Strikingly, gene deletion occurred even when the transferred cells were left in a naive state, suggesting that gene deletion occurs independent of T cell activation. This protocol thus expands CRISPR-based probing of gene function beyond models of robust T cell activation, to encompass both naive T cell homeostasis and models of weak activation, such as tolerance and tumour models.

immunology↗