Dynamic scRNA-seq of live human pancreatic slices reveals functional endocrine cell neogenesis through an intermediate ducto-acinar stage.

Cell metabolism Pub Date : 2023-11-07 Epub Date: 2023-10-27 DOI:10.1016/j.cmet.2023.10.001
Mayur Doke, Silvia Álvarez-Cubela, Dagmar Klein, Isabella Altilio, Joseph Schulz, Luciana Mateus Gonçalves, Joana Almaça, Christopher A Fraker, Alberto Pugliese, Camillo Ricordi, Mirza M F Qadir, Ricardo L Pastori, Juan Domínguez-Bendala
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Abstract

Human pancreatic plasticity is implied from multiple single-cell RNA sequencing (scRNA-seq) studies. However, these have been invariably based on static datasets from which fate trajectories can only be inferred using pseudotemporal estimations. Furthermore, the analysis of isolated islets has resulted in a drastic underrepresentation of other cell types, hindering our ability to interrogate exocrine-endocrine interactions. The long-term culture of human pancreatic slices (HPSs) has presented the field with an opportunity to dynamically track tissue plasticity at the single-cell level. Combining datasets from same-donor HPSs at different time points, with or without a known regenerative stimulus (BMP signaling), led to integrated single-cell datasets storing true temporal or treatment-dependent information. This integration revealed population shifts consistent with ductal progenitor activation, blurring of ductal/acinar boundaries, formation of ducto-acinar-endocrine differentiation axes, and detection of transitional insulin-producing cells. This study provides the first longitudinal scRNA-seq analysis of whole human pancreatic tissue, confirming its plasticity in a dynamic fashion.

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活的人类胰腺切片的动态scRNA-seq揭示了通过腺泡导管中期的功能性内分泌细胞新生。
多个单细胞RNA测序(scRNA-seq)研究暗示了人类胰腺的可塑性。然而,这些都是基于静态数据集的,只能使用伪时间估计来推断命运轨迹。此外,对分离的胰岛的分析导致其他细胞类型的代表性严重不足,阻碍了我们询问外分泌-内分泌相互作用的能力。人类胰腺切片(HPSs)的长期培养为该领域提供了在单细胞水平上动态跟踪组织可塑性的机会。将来自不同时间点的相同供体HPS的数据集结合起来,无论是否有已知的再生刺激(BMP信号),都会产生存储真正的时间或治疗依赖性信息的集成单细胞数据集。这种整合揭示了与导管祖细胞激活、导管/腺泡边界模糊、导管-腺泡内分泌分化轴的形成以及过渡胰岛素产生细胞的检测一致的群体变化。这项研究首次对整个人类胰腺组织进行了纵向scRNA-seq分析,以动态方式证实了其可塑性。
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