Mitochondrial gene expression in single cells shape pancreatic beta cells' sub-populations and explain variation in insulin pathway

Ex vivo immunocapture and functional characterization of cell-type-specific mitochondria using MitoTag mice

Mitochondria are key bioenergetic organelles involved in many biosynthetic and signaling pathways. However, their differential contribution to specific functions of cells within complex tissues is difficult to dissect with current methods. The present protocol addresses this need by enabling the ex vivo immunocapture of cell-type-specific mitochondria directly from their tissue context through a MitoTag reporter mouse. While other available methods were developed for bulk mitochondria isolation or more abundant cell-type-specific mitochondria, this protocol was optimized for the selective isolation of functional mitochondria from medium-to-low-abundant cell types in a heterogeneous tissue, such as the central nervous system. The protocol has three major parts: First, mitochondria of a cell type of interest are tagged via an outer mitochondrial membrane eGFP by crossing MitoTag mice to a cell-type-specific Cre-driver line or by delivery of viral vectors for Cre expression. Second, homogenates are prepared from relevant tissues by nitrogen cavitation, from which tagged organelles are immunocaptured using magnetic microbeads. Third, immunocaptured mitochondria are used for downstream assays, e.g., to probe respiratory capacity or calcium handling, revealing cell-type-specific mitochondrial diversity in molecular composition and function. The MitoTag approach enables the identification of marker proteins to label cell-type-specific organelle populations in situ, elucidates cell-type-enriched mitochondrial metabolic and signaling pathways, and reveals functional mitochondrial diversity between adjacent cell types in complex tissues, such as the brain. Apart from establishing the mouse colony (6-8 weeks without import), the immunocapture protocol takes 2 h and functional assays require 1-2 h.

Type I Diabetes Pathoetiology and Pathophysiology: Roles of the Gut Microbiome, Pancreatic Cellular Interactions, and the 'Bystander' Activation of Memory CD8+ T Cells

Type 1 diabetes mellitus (T1DM) arises from the failure of pancreatic β-cells to produce adequate insulin, usually as a consequence of extensive pancreatic β-cell destruction. T1DM is classed as an immune-mediated condition. However, the processes that drive pancreatic β-cell apoptosis remain to be determined, resulting in a failure to prevent ongoing cellular destruction. Alteration in mitochondrial function is clearly the major pathophysiological process underpinning pancreatic β-cell loss in T1DM. As with many medical conditions, there is a growing interest in T1DM as to the role of the gut microbiome, including the interactions of gut bacteria with Candida albicans fungal infection. Gut dysbiosis and gut permeability are intimately associated with raised levels of circulating lipopolysaccharide and suppressed butyrate levels, which can act to dysregulate immune responses and systemic mitochondrial function. This manuscript reviews broad bodies of data on T1DM pathophysiology, highlighting the importance of alterations in the mitochondrial melatonergic pathway of pancreatic β-cells in driving mitochondrial dysfunction. The suppression of mitochondrial melatonin makes pancreatic β-cells susceptible to oxidative stress and dysfunctional mitophagy, partly mediated by the loss of melatonin's induction of PTEN-induced kinase 1 (PINK1), thereby suppressing mitophagy and increasing autoimmune associated major histocompatibility complex (MHC)-1. The immediate precursor to melatonin, N-acetylserotonin (NAS), is a brain-derived neurotrophic factor (BDNF) mimic, via the activation of the BDNF receptor, TrkB. As both the full-length and truncated TrkB play powerful roles in pancreatic β-cell function and survival, NAS is another important aspect of the melatonergic pathway relevant to pancreatic β-cell destruction in T1DM. The incorporation of the mitochondrial melatonergic pathway in T1DM pathophysiology integrates wide bodies of previously disparate data on pancreatic intercellular processes. The suppression of Akkermansia muciniphila, Lactobacillus johnsonii, butyrate, and the shikimate pathway-including by bacteriophages-contributes to not only pancreatic β-cell apoptosis, but also to the bystander activation of CD8⁺ T cells, which increases their effector function and prevents their deselection in the thymus. The gut microbiome is therefore a significant determinant of the mitochondrial dysfunction driving pancreatic β-cell loss as well as 'autoimmune' effects derived from cytotoxic CD8⁺ T cells. This has significant future research and treatment implications.

High-frequency and functional mitochondrial DNA mutations at the single-cell level

Decline in mitochondrial function underlies aging and age-related diseases, but the role of mitochondrial DNA (mtDNA) mutations in these processes remains elusive. To investigate patterns of mtDNA mutations, it is particularly important to quantify mtDNA mutations and their associated pathogenic effects at the single-cell level. However, existing single-cell mtDNA sequencing approaches remain inefficient due to high cost and low mtDNA on-target rates. In this study, we developed a cost-effective mtDNA targeted-sequencing protocol called single-cell sequencing by targeted amplification of multiplex probes (scSTAMP) and experimentally validated its reliability. We then applied our method to assess single-cell mtDNA mutations in 768 B lymphocytes and 768 monocytes from a 76-y-old female. Across 632 B lymphocyte and 617 monocytes with medium mtDNA coverage over >100×, our results indicated that over 50% of cells carried at least one mtDNA mutation with variant allele frequencies (VAFs) over 20%, and that cells carried an average of 0.658 and 0.712 such mutation for B lymphocytes and monocytes, respectively. Surprisingly, more than 20% of the observed mutations had VAFs of over 90% in either cell population. In addition, over 60% of the mutations were in protein-coding genes, of which over 70% were nonsynonymous, and more than 50% of the nonsynonymous mutations were predicted to be highly pathogenic. Interestingly, about 80% of the observed mutations were singletons in the respective cell populations. Our results revealed mtDNA mutations with functional significance might be prevalent at advanced age, calling further investigation on age-related mtDNA mutation dynamics at the single-cell level.

Single-cell transcriptome reveals diversity of Müller cells with different metabolic-mitochondrial signatures in normal and degenerated macula

Müller cell is the most abundant glial cell in mammalian retina, supporting the functions of photoreceptors and other retinal neurons via maintaining environmental homeostasis. In response to injury and/or neuronal degeneration, Müller cells undergo morphological and functional alternations, known as reactive gliosis documented in multiple retinal diseases, including age-related macular degeneration (AMD), retinitis pigmentosa, diabetic retinopathy, and traumatic retinal detachment. But the functional consequences of Müller glia cell reactivation or even the regulatory networks of the retinal gliosis are still controversial. In this study, we reveal different subpopulations of Müller cells with distinct metabolic-mitochondrial signatures by integrating single cell transcriptomic data from Early AMD patients and healthy donors. Our results show that a portion of Müller cells exhibits low mitochondrial DNA (mtDNA) expressions, reduced protein synthesis, impaired homeostatic regulation, decreased proliferative ability but enhanced proangiogenic function. Interestingly, the major alternation of Müller cells in Early AMD retina is the change of subpopulation abundance, rather than generation of new subcluster. Transcription factor enrichment analysis further highlights the key regulators of metabolic-mitochondrial states of Müller glias in Early AMD patients especially. Our study demonstrates new characteristics of retinal gliosis associated with Early AMD and suggests the possibility to prevent degeneration by intervening mitochondrial functions of Müller cells.

Single-cell RNA sequencing analysis of T helper cell differentiation and heterogeneity

Single-cell transcriptomics has emerged as a powerful tool to investigate cells' biological landscape and focus on the expression profile of individual cells. Major advantage of this approach is an analysis of highly complex and heterogeneous cell populations, such as a specific subpopulation of T helper cells that are known to differentiate into distinct subpopulations. The need for distinguishing the specific expression profile is even more important considering the T cell plasticity. However, importantly, the universal pipelines for single-cell analysis are usually not sufficient for every cell type. Here, the aims are to analyze the diversity of T cell phenotypes employing classical in vitro cytokine-mediated differentiation of human T cells isolated from human peripheral blood by single-cell transcriptomic approach with support of labelled antibodies and a comprehensive bioinformatics analysis using combination of Seurat, Nebulosa, GGplot and others. The results showed high expression similarities between Th1 and Th17 phenotype and very distinct Th2 expression profile. In a case of Th2 highly specific marker genes SPINT2, TRIB3 and CST7 were expressed. Overall, our results demonstrate how donor difference, Th plasticity and cell cycle influence the expression profiles of distinct T cell populations. The results could help to better understand the importance of each step of the analysis when working with T cell single-cell data and observe the results in a more practical way by using our analyzed datasets.

Calcium-dependent transcriptional changes in human pancreatic islet cells reveal functional diversity in islet cell subtypes

AIMS/HYPOTHESIS

Pancreatic islets depend on cytosolic calcium (Ca²⁺) to trigger the secretion of glucoregulatory hormones and trigger transcriptional regulation of genes important for islet response to stimuli. To date, there has not been an attempt to profile Ca²⁺-regulated gene expression in all islet cell types. Our aim was to construct a large single-cell transcriptomic dataset from human islets exposed to conditions that would acutely induce or inhibit intracellular Ca²⁺ signalling, while preserving biological heterogeneity.

METHODS

We exposed intact human islets from three donors to the following conditions: (1) 2.8 mmol/l glucose; (2) 16 mmol/l glucose and 40 mmol/l KCl to maximally stimulate Ca²⁺ signalling; and (3) 16 mmol/l glucose, 40 mmol/l KCl and 5 mmol/l EGTA (Ca²⁺ chelator) to inhibit Ca²⁺ signalling, for 1 h. We sequenced 68,650 cells from all islet cell types, and further subsetted the cells to form an endocrine cell-specific dataset of 59,373 cells expressing INS, GCG, SST or PPY. We compared transcriptomes across conditions to determine the differentially expressed Ca²⁺-regulated genes in each endocrine cell type, and in each endocrine cell subcluster of alpha and beta cells.

RESULTS

Based on the number of Ca²⁺-regulated genes, we found that each alpha and beta cell cluster had a different magnitude of Ca²⁺ response. We also showed that polyhormonal clusters expressing both INS and GCG, or both INS and SST, are defined by Ca²⁺-regulated genes specific to each cluster. Finally, we identified the gene PCDH7 from the beta cell clusters that had the highest number of Ca²⁺-regulated genes, and showed that cells expressing cell surface PCDH7 protein have enhanced glucose-stimulated insulin secretory function.

CONCLUSIONS/INTERPRETATION

Here we use our large-scale, multi-condition, single-cell dataset to show that human islets have cell-type-specific Ca²⁺-regulated gene expression profiles, some of them specific to subpopulations. In our dataset, we identify PCDH7 as a novel marker of beta cells having an increased number of Ca²⁺-regulated genes and enhanced insulin secretory function.

DATA AVAILABILITY

A searchable and user-friendly format of the data in this study, specifically designed for rapid mining of single-cell RNA sequencing data, is available at https://lynnlab.shinyapps.io/Human_Islet_Atlas/ . The raw data files are available at NCBI Gene Expression Omnibus (GSE196715).

Discovering Cellular Mitochondrial Heteroplasmy Heterogeneity with Single Cell RNA and ATAC Sequencing

Next-generation sequencing technologies have revolutionised the study of biological systems by enabling the examination of a broad range of tissues. Its application to single-cell genomics has generated a dynamic and evolving field with a vast amount of research highlighting heterogeneity in transcriptional, genetic and epigenomic state between cells. However, compared to these aspects of cellular heterogeneity, relatively little has been gleaned from single-cell datasets regarding cellular mitochondrial heterogeneity. Single-cell sequencing techniques can provide coverage of the mitochondrial genome which allows researchers to probe heteroplasmies at the level of the single cell, and observe interactions with cellular function. In this review, we give an overview of two popular single-cell modalities-single-cell RNA sequencing and single-cell ATAC sequencing-whose throughput and widespread usage offers researchers the chance to probe heteroplasmy combined with cell state in detailed resolution across thousands of cells. After summarising these technologies in the context of mitochondrial research, we give an overview of recent methods which have used these approaches for discovering mitochondrial heterogeneity. We conclude by highlighting current limitations of these approaches and open problems for future consideration.