Aging compromises human islet beta cell function and identity by decreasing transcription factor activity and inducing ER stress

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Abstract

Pancreatic islet beta cells are essential for maintaining glucose homeostasis. To understand the impact of aging on beta cells, we performed meta-analysis of single-cell RNA sequencing datasets, transcription factor (TF) regulon analysis, high-resolution confocal microscopy, and measured insulin secretion from nondiabetic donors spanning most of the human life span. This revealed the range of molecular and functional changes that occur during beta cell aging, including the transcriptional deregulation that associates with cellular immaturity and reorganization of beta cell TF networks, increased gene transcription rates, and reduced glucose-stimulated insulin release. These alterations associate with activation of endoplasmic reticulum (ER) stress and autophagy pathways. We propose that a chronic state of ER stress undermines old beta cell structure function to increase the risk of beta cell failure and type 2 diabetes onset as humans age.

Abstract

As human beta cells age, they become less functional and accumulate cellular stress due to loss of transcriptional control.

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Most cited references 76

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Comprehensive Integration of Single-Cell Data

Tim Stuart, Andrew Butler, Paul Hoffman … (2019)

Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.

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The Hallmarks of Aging

Carlos López-Otín, Maria Blasco, Linda Partridge … (2013)

Aging is characterized by a progressive loss of physiological integrity, leading to impaired function and increased vulnerability to death. This deterioration is the primary risk factor for major human pathologies, including cancer, diabetes, cardiovascular disorders, and neurodegenerative diseases. Aging research has experienced an unprecedented advance over recent years, particularly with the discovery that the rate of aging is controlled, at least to some extent, by genetic pathways and biochemical processes conserved in evolution. This Review enumerates nine tentative hallmarks that represent common denominators of aging in different organisms, with special emphasis on mammalian aging. These hallmarks are: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication. A major challenge is to dissect the interconnectedness between the candidate hallmarks and their relative contributions to aging, with the final goal of identifying pharmaceutical targets to improve human health during aging, with minimal side effects. Copyright © 2013 Elsevier Inc. All rights reserved.

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SCENIC: Single-cell regulatory network inference and clustering

Sara Aibar, Carmen Bravo Gonzalez-Blas, Thomas Moerman … (2017)

Although single-cell RNA-seq is revolutionizing biology, data interpretation remains a challenge. We present SCENIC for the simultaneous reconstruction of gene regulatory networks and identification of cell states. We apply SCENIC to a compendium of single-cell data from tumors and brain, and demonstrate that the genomic regulatory code can be exploited to guide the identification of transcription factors and cell states. SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity.

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Author and article information

Contributors

Shristi Shrestha:

ORCID: https://orcid.org/0000-0003-4519-1712

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Galina Erikson: Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Software

James Lyon:

ORCID: https://orcid.org/0000-0001-7737-5183

Role: Resources

Aliya F. Spigelman: Role: Investigation

Austin Bautista: Role: Formal analysisRole: InvestigationRole: ResourcesRole: Validation

Jocelyn E. Manning Fox:

ORCID: https://orcid.org/0000-0002-4157-2094

Role: Data curationRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing - review & editing

Cristiane dos Santos:

ORCID: https://orcid.org/0000-0002-6859-3784

Role: InvestigationRole: Validation

Maxim Shokhirev:

ORCID: https://orcid.org/0000-0002-8379-8657

Role: ConceptualizationRole: Data curationRole: ResourcesRole: SupervisionRole: Writing - original draftRole: Writing - review & editing

Jean-Philippe Cartailler:

ORCID: https://orcid.org/0000-0002-0312-2391

Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: ValidationRole: VisualizationRole: Writing - original draft

Martin W. Hetzer: Role: ConceptualizationRole: MethodologyRole: Writing - original draft

Patrick E. MacDonald:

ORCID: https://orcid.org/0000-0002-5439-6288

Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing - review & editing

Rafael Arrojo e Drigo:

ORCID: https://orcid.org/0000-0001-7712-013X

Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Journal

Journal ID (nlm-ta): Sci Adv

Journal ID (iso-abbrev): Sci Adv

Journal ID (publisher-id): sciadv

Journal ID (hwp): advances

Title: Science Advances

Publisher: American Association for the Advancement of Science

ISSN (Electronic): 2375-2548

Publication date Collection: October 2022

Publication date (Electronic, pub): 05 October 2022

Volume: 8

Issue: 40

Electronic Location Identifier: eabo3932

Affiliations

[ ¹ ]Creative Data Solutions, Vanderbilt Center for Stem Cell Biology, Nashville, TN 37232, USA.

[ ² ]Integrative Genomics and Bioinformatics Core, Salk Institute of Biological Studies, La Jolla, CA 92037, USA.

[ ³ ]Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta T6G2E1, Canada.

[ ⁴ ]Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232, USA.

[ ⁵ ]Molecular and Cell Biology Laboratory, Salk Institute of Biological Studies, La Jolla, CA 92037, USA.

Author notes

[* ]Corresponding author. Email: r.drigo@ 123456vanderbilt.edu

Author information

Shristi Shrestha https://orcid.org/0000-0003-4519-1712

James Lyon https://orcid.org/0000-0001-7737-5183

Jocelyn E. Manning Fox https://orcid.org/0000-0002-4157-2094

Cristiane dos Santos https://orcid.org/0000-0002-6859-3784

Maxim Shokhirev https://orcid.org/0000-0002-8379-8657

Jean-Philippe Cartailler https://orcid.org/0000-0002-0312-2391

Patrick E. MacDonald https://orcid.org/0000-0002-5439-6288

Rafael Arrojo e Drigo https://orcid.org/0000-0001-7712-013X

Article

Publisher ID: abo3932

DOI: 10.1126/sciadv.abo3932

PMC ID: 9534504

PubMed ID: 36197983

SO-VID: 85cb8e28-32ad-4916-ba7a-62b38f16dd96

Copyright © Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

History

Date received : 31 January 2022

Date accepted : 17 August 2022

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000054, National Cancer Institute;

Award ID: P30 014195

Funded by: FundRef http://dx.doi.org/10.13039/100007028, Leona M. and Harry B. Helmsley Charitable Trust;

Funded by: Human Islet Research Network RRID SCR_;

Award ID: UC4-DK-112217

Funded by: Human Islet Research Network RRID SCR_;

Award ID: U01-DK-123594

Funded by: Human Islet Research Network RRID SCR_;

Award ID: UC4-DK-112232

Funded by: Human Islet Research Network RRID SCR_;

Award ID: U01-DK-123716

Funded by: National Institutes of Health and Human Islet Research Network;

Award ID: U01DK120447

Funded by: New Investigator Pilot Program in Bioinformatics;

Award ID: U24DK097771

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Copyeditor Vivian Hernandez

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Aging compromises human islet beta cell function and identity by decreasing transcription factor activity and inducing ER stress

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Most cited references 76

Comprehensive Integration of Single-Cell Data

The Hallmarks of Aging

SCENIC: Single-cell regulatory network inference and clustering

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Cited by 13

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