Single Nucleus RNA Sequencing of Human Pancreatic Islets <i>In Vitro</i> and <i>In Vivo</i> Identifies New Gene Sets and Three β-Cell Subpopulations with Different Transcriptional Profile

Kang, Randy B; Li, Yansui; Rosselot, Carolina; Zhang, Tuo; Siddiq, Mustafa M; Rajbhandari, Prashant; Stewart, Andrew F.; Scott, Donald K.; Garcı́a-Ocaña, Adolfo; Lu, Geming

doi:10.1101/2022.05.22.492974

Cited by 3 publications

(4 citation statements)

References 59 publications

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“…Group 1 contained genes implicated in β-cell metabolic stress recovery, such as ATP production related genes 101 ( Figure 5g , Supplementary Table S7 ). The negative correlation between expression of group 1 and groups 3/5 is in accordance with previously reported cycling of β-cells between insulin production and recovery in mouse and human 101, 106, 107 . As group 1 genes, including multiple mitochondrial genes, β-cell maturation and function genes ( Ucn3 , Ftl1 , Cd63 , Scg2) 73, 108 , and protective genes ( Nupr1 , Atp2a2 , Atf5 ) 109–111 , are involved in healthy metabolic stress recovery they may be of interest for T2D therapy.…”

Section: Resultssupporting

confidence: 92%

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

Hrovatin

Bastidas-Ponce

Bakhti

et al. 2022

Preprint

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Multiple single-cell RNA sequencing (scRNA-seq) datasets have been generated to study pancreatic islet cells during development, homeostasis, and diabetes progression. However, despite the time and resources invested into the past scRNA-seq studies, there is still no consensus on islet cell states and associated pathways in health and dysfunction as well as the value of frequently used preclinical mouse diabetes models. Since these challenges can be only resolved with a joint analysis of 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 autoimmune type 1 diabetes (T1D) model (NOD), gluco-/lipotoxicity T2D model (db/db), and chemical streptozotocin (STZ) β-cell ablation model. MIA is a curated resource that enables interactive exploration of gene expression and transfer of cell types and states. We use MIA to obtain new insights into islet cells in health and disease that cannot be reached from individual datasets. Based on the MIA β-cell landscape we report cross-publication differences between previously suggested marker genes of individual phenotypes. We further show that in the STZ model β-cells transcriptionally correlate to human T2D and mouse db/db model β-cells, but are less similar to human T1D and mouse NOD model β-cells. We define new cell states involved in disease progression across diabetes models. We also observe different pathways shared between immature, aged, and diabetes model β-cell states. In conclusion, our work presents the first comprehensive analysis of β-cell responses to different stressors, providing a roadmap for the understanding of β-cell plasticity, compensation, and demise.

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Section: Resultssupporting

confidence: 92%

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

Hrovatin

Bastidas-Ponce

Bakhti

et al. 2022

Preprint

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“…We utilized RNAscope Multiplex Fluorescent v2 Assays (ACD biosciences). We followed the manufacturers protocol with minor modifications (Kang et al, 2023). Spinal Cord sections were post-fixed with 4%PFA, washed in PBS.…”

Section: Rnascopementioning

confidence: 99%

Spinal cord injury regulates circular RNA expression in axons

Siddiq,

Toro,

Johnson

et al. 2023

Front. Mol. Neurosci.

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IntroductionNeurons transport mRNA and translational machinery to axons for local translation. After spinal cord injury (SCI), de novo translation is assumed to enable neurorepair. Knowledge of the identity of axonal mRNAs that participate in neurorepair after SCI is limited. We sought to identify and understand how axonal RNAs play a role in axonal regeneration.MethodsWe obtained preparations enriched in axonal mRNAs from control and SCI rats by digesting spinal cord tissue with cold-active protease (CAP). The digested samples were then centrifuged to obtain a supernatant that was used to identify mRNA expression. We identified differentially expressed genes (DEGS) after SCI and mapped them to various biological processes. We validated the DEGs by RT-qPCR and RNA-scope.ResultsThe supernatant fraction was highly enriched for mRNA from axons. Using Gene Ontology, the second most significant pathway for all DEGs was axonogenesis. Among the DEGs was Rims2, which is predominately a circular RNA (circRNA) in the CNS. We show that Rims2 RNA within spinal cord axons is circular. We found an additional 200 putative circRNAs in the axonal-enriched fraction. Knockdown in primary rat cortical neurons of the RNA editing enzyme ADAR1, which inhibits formation of circRNAs, significantly increased axonal outgrowth and increased the expression of circRims2. Using Rims2 as a prototype we used Circular RNA Interactome to predict miRNAs that bind to circRims2 also bind to the 3’UTR of GAP-43, PTEN or CREB1, all known regulators of axonal outgrowth. Axonally-translated GAP-43 supports axonal elongation and we detect GAP-43 mRNA in the rat axons by RNAscope.DiscussionBy enriching for axonal RNA, we detect SCI induced DEGs, including circRNA such as Rims2. Ablation of ADAR1, the enzyme that regulates circRNA formation, promotes axonal outgrowth of cortical neurons. We developed a pathway model using Circular RNA Interactome that indicates that Rims2 through miRNAs can regulate the axonal translation GAP-43 to regulate axonal regeneration. We conclude that axonal regulatory pathways will play a role in neurorepair.

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“…Xu et al 2022; Olaniru et al 2022; Lin et al 2021) and adult pancreas (Liu et al 2014; Baron et al 2016; Muraro et al 2016; Segerstolpe et al 2016; Y. J. Wang et al 2016; Xin et al 2016; Lawlor et al 2017; Enge et al 2017; Han et al 2020; Kang et al 2022; Wigger et al 2021). Efforts have also been made to map cellular identity during pancreas development starting from human pluripotent stem cells (Gonçalves et al 2021; Rezania et al 2014; Hrvatin et al 2014; Z.…”

Section: Introductionmentioning

confidence: 99%

“…Efforts have also been made to map cellular identity during pancreas development starting from human pluripotent stem cells (Gonçalves et al 2021; Rezania et al 2014; Hrvatin et al 2014; Z. Zhu et al 2016; Augsornworawat et al 2020; Hogrebe et al 2021; Peterson et al 2020; Veres et al 2019; Balboa et al 2022; Krentz et al 2018; Kang et al 2022; Augsornworawat et al 2022; Budnik et al 2022). Taken together, these studies provide an opportunity to better understand the establishment and maintenance of cellular identity among different pancreatic cell types.…”

Section: Introductionmentioning

confidence: 99%

Predicting the Key Regulators of Cell Identity in Human Adult Pancreas

Vanheer¹,

Schiavo

Haele

et al. 2020

Preprint

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SUMMARYCellular identity during development is under the control of transcription factors that form gene regulatory networks. However, the transcription factors and gene regulatory networks underlying cellular identity in the human adult pancreas remain largely unexplored. Here, we integrate multiple single-cell RNA sequencing datasets of the human adult pancreas, totaling 7393 cells, and comprehensively reconstruct gene regulatory networks. We show that a network of 142 transcription factors forms distinct regulatory modules that characterize pancreatic cell types. We present evidence that our approach identifies key regulators of cell identity in the human adult pancreas. We predict that HEYL and JUND are active in acinar and alpha cells, respectively, and show that these proteins are present in the human adult pancreas as well as in human induced pluripotent stem cell-derived pancreatic cells. The comprehensive gene regulatory network atlas can be explored interactively online. We anticipate our analysis to be the starting point for a more sophisticated dissection of how transcription factors regulate cell identity in the human adult pancreas. Furthermore, given that transcription factors are major regulators of embryo development and are often perturbed in diseases, a comprehensive understanding of how transcription factors work will be relevant in development and disease biology.HIGHLIGHTS-Reconstruction of gene regulatory networks for human adult pancreatic cell types-An interactive resource to explore and visualize gene expression and regulatory states-Predicting putative transcription factors driving pancreatic cell identity-HEYL and JUND as candidate regulators of acinar and alpha cell identity, respectively

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Single Nucleus RNA Sequencing of Human Pancreatic Islets In Vitro and In Vivo Identifies New Gene Sets and Three β-Cell Subpopulations with Different Transcriptional Profile

Cited by 3 publications

References 59 publications

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

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

Spinal cord injury regulates circular RNA expression in axons

Predicting the Key Regulators of Cell Identity in Human Adult Pancreas

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