Non-viral intron knock-ins for targeted gene integration into human T cells and for T-cell selection
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Pancreatic organogenesis mapped through space and time
The spatial organization of cells within a tissue is dictated throughout dynamic developmental processes. We sought to understand whether cells geometrically coordinate with one another throughout development to achieve their organization. The pancreas is a complex cellular organ with a particular spatial organization. Signals from the mesenchyme, neurons, and endothelial cells instruct epithelial cell differentiation during pancreatic development. To understand the cellular diversity and spatial organization of the developing pancreatic niche, we mapped the spatial relationships between single cells over time. We found that four transcriptionally unique subtypes of mesenchyme in the developing pancreas spatially coordinate throughout development, with each subtype at fixed locations in space and time in relation to other cells, including beta cells, vasculature, and epithelial cells. Our work provides insight into the mechanisms of pancreatic development by showing that cells are organized in a space and time manner.
Comparative evaluation of SNVs, indels, and structural variations detected with short- and long-read sequencing data
Short- and long-read sequencing technologies are routinely used to detect DNA variants, including SNVs, indels, and structural variations (SVs). However, the differences in the quality and quantity of variants detected between short- and long-read data are not fully understood. In this study, we comprehensively evaluated the variant calling performance of short- and long-read-based SNV, indel, and SV detection algorithms (6 for SNVs, 12 for indels, and 13 for SVs) using a novel evaluation framework incorporating manual visual inspection. The results showed that indel-insertion calls greater than 10 bp were poorly detected by short-read-based detection algorithms compared to long-read-based algorithms; however, the recall and precision of SNV and indel-deletion detection were similar between short- and long-read data. The recall of SV detection with short-read-based algorithms was significantly lower in repetitive regions, especially for small- to intermediate-sized SVs, than that detected with long-read-based algorithms. In contrast, the recall and precision of SV detection in nonrepetitive regions were similar between short- and long-read data. These findings suggest the need for refined strategies, such as incorporating multiple variant detection algorithms, to generate a more complete set of variants using short-read data.
SEED-Selection enables high-efficiency enrichment of primary T cells edited at multiple loci
Engineering T cell specificity and function at multiple loci can generate more effective cellular therapies, but current manufacturing methods produce heterogenous mixtures of partially engineered cells. Here we develop a one-step process to enrich unlabeled cells containing knock-ins at multiple target loci using a family of repair templates named synthetic exon expression disruptors (SEEDs). SEEDs associate transgene integration with the disruption of a paired target endogenous surface protein while preserving target expression in nonmodified and partially edited cells to enable their removal (SEED-Selection). We design SEEDs to modify three critical loci encoding T cell specificity, coreceptor expression and major histocompatibility complex expression. The results demonstrate up to 98% purity after selection for individual modifications and up to 90% purity for six simultaneous edits (three knock-ins and three knockouts). This method is compatible with existing clinical manufacturing workflows and can be readily adapted to other loci to facilitate production of complex gene-edited cell therapies.
Targeting the splicing factor SNRPB inhibits endometrial cancer progression by retaining the POLD1 intron
Dysregulated alternative splicing has been closely linked to the initiation and progression of tumors. Nevertheless, the precise molecular mechanisms through which splicing factors regulate endometrial cancer progression are still not fully understood. This study demonstrated elevated expression of the splicing factor SNRPB in endometrial cancer samples. Furthermore, our findings indicate that high SNRPB expression is correlated with poor prognosis in patients with endometrial cancer. Functionally, SNRPB inhibition hindered the proliferative and metastatic capacities of endometrial cancer cells. Mechanistically, we revealed that SNRPB knockdown decreased POLD1 expression and that POLD1 intron 22 was retained after SNRPB silencing in endometrial cancer cells, as determined via RNA sequencing data analysis. The retained intron 22 of POLD1 created a premature termination codon, leading to the absence of amino acids 941–1,107 and the loss of the site of interaction with PCNA, which is essential for POLD1 enzyme activity. In addition, POLD1 depletion decreased the increase in the malignancy of endometrial cancer cells overexpressing SNRPB. Furthermore, miR-654-5p was found to bind directly to the 3′ untranslated region of SNRPB, resulting in SNRPB expression inhibition in endometrial cancer. Antisense oligonucleotide-mediated SNRPB inhibition led to a decrease in the growth capacity of a cell-derived xenograft model and a patient with endometrial cancer-derived xenograft model. Overall, SNRPB promotes the efficient splicing of POLD1 by regulating intron retention, ultimately contributing to high POLD1 expression in endometrial cancer. The oncogenic SNRPB–POLD1 axis is an interesting therapeutic target for endometrial cancer, and antisense oligonucleotide-mediated silencing of SNRPB may constitute a promising therapeutic approach for treating patients with endometrial cancer.
Dispersal, habitat filtering, and eco-evolutionary dynamics as drivers of local and global wetland viral biogeography
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