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Biology subjects

Migliorini, A.

Publications and source records attributed to Migliorini, A..

2 recordsLinked to original sources

Macrophages heterogeneity and significance during human fetal pancreatic development

Organogenesis is a complex process that relies on a dynamic interplay between extrinsic factors originating from the microenvironment and intrinsic factors specific to the tissue. For the endocrine cells of the islet of Langerhans, the local microenvironment consists of various cell types including pancreatic acinar and ductal cells as well as neuronal, immune, endothelial, and stromal cells. Interestingly, hematopoietic cells have been detected in human pancreas as early as 6 post-conception weeks (PCW)1,2, but whether they play a role during islet formation in humans remains largely unknown. To shed light on this question, we performed single nuclei RNA sequencing of the human fetal pancreas during the early weeks of the second trimester, specifically focusing on the molecular interaction between the hematopoietic niche and the pancreatic epithelium. Our analysis identified a wide range of hematopoietic cells as well as two distinct subsets of macrophages that are unique to the fetal pancreas and absent in neonatal or adult pancreatic tissues. Leveraging this discovery, we developed a co-culture system of hESC-derived endocrine-macrophage organoids to model their interaction in vitro. Remarkably, we found that macrophages promoted the differentiation and viability of developing endocrine cells in vitro and enhanced tissue engraftment in immunocompromised mice, supporting a role for these cells in future tissue engineering strategies for diabetes.

developmental biology↗

Delineating mouse β-cell identity during lifetime and in diabetes with a single cell atlas

Multiple pancreatic islet single-cell RNA sequencing (scRNA-seq) datasets have been generated to study development, homeostasis, and diabetes. However, there is no consensus on cell states and pathways across conditions as well as the value of preclinical mouse models. Since these challenges can only be resolved by jointly analyzing multiple datasets, we present a scRNA-seq cross-condition mouse islet atlas (MIA). We integrated over 300,000 cells from nine datasets with 56 samples, varying in age, sex, and diabetes models, including an autoimmune type 1 diabetes (T1D) model (NOD), a gluco-/lipotoxicity T2D model (db/db), and a chemical streptozotocin (STZ) {beta}-cell ablation model. MIA is a curated resource for interactive exploration and computational querying, providing new insights inaccessible from individual datasets. The {beta}-cell landscape of MIA revealed new disease progression cell states and cross-publication differences between previously suggested marker genes. We show that in the STZ model {beta}-cells transcriptionally correlate to human T2D and mouse db/db, but are less similar to human T1D and mouse NOD. We observe different pathways shared between immature, aged, and diabetes model {beta}-cells. In conclusion, our work presents the first comprehensive analysis of {beta}-cell responses to different stressors, providing a roadmap for the understanding of {beta}-cell plasticity, compensation, and demise.

bioinformatics↗