scholarly journals Multi-modal single cell analysis reveals brain immune landscape plasticity during aging and gut microbiota dysbiosis

2020 ◽  
Author(s):  
Samantha M. Golomb ◽  
Ian H. Guldner ◽  
Anqi Zhao ◽  
Qingfei Wang ◽  
Bhavana Palakurthi ◽  
...  

ABSTRACTThe brain contains a diverse array of immune cell types. The phenotypic and functional plasticity of brain immune cells collectively contribute to brain tissue homeostasis and disease progression. Immune cell plasticity is profoundly influenced by local tissue microenvironment cues and systemic factors. Yet, the transcriptional mechanism by which systemic stimuli, such as aging and gut microbiota dysbiosis, reshape brain immune cell plasticity and homeostasis has not been fully delineated. Using Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq), we analyzed compositional and transcriptional changes of the brain immune landscape in response to aging and gut dysbiosis. We first examined the discordance between canonical surface marker-defined immune cell types (Cell-ID) and their transcriptome signatures, which suggested transcriptional plasticity among immune cells despite sharing the same cell surface markers. Specifically, inflammatory and patrolling Ly6C+ monocytes were shifted predominantly to a pro-inflammatory transcriptional program in the aged brain, while brain ILCs shifted toward an ILC2 transcriptional profile. Finally, aging led to an increase of ILC-like cells expressing a T memory stemness (Tscm) signature in the brain. Antibiotics (ABX)-induced gut dysbiosis reduced the frequency of ILCs exhibiting Tscm-like properties in the aged mice, but not in the young mice. Enabled by high-resolution single-cell molecular phenotyping, our study revealed that systemic changes due to aging and gut dysbiosis prime the brain environment for an increased propensity for neuroinflammation, which provided insights into gut dysbiosis in age-related neurological diseases.Manuscript SummaryGolomb et al. performed Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq) on immune cells from the brains of young and aged mice with and without antibiotics-induced gut dysbiosis. High resolution, single cell immunophenotyping enabled the dissection of extensive transcriptional plasticity of canonically identified monocytes and innate lymphoid cells (ILCs) in the aged brain. Through differential gene expression and trajectory inference analyses, the authors revealed tissue microenvironment-dependent cellular responses influenced by aging and gut dysbiosis that may potentiate neuroinflammatory diseases.Graphical Abstract

2021 ◽  
Author(s):  
Zhibin Li ◽  
chengcheng Sun ◽  
Fei Wang ◽  
Xiran Wang ◽  
Jiacheng Zhu ◽  
...  

Background: Immune cells play important roles in mediating immune response and host defense against invading pathogens. However, insights into the molecular mechanisms governing circulating immune cell diversity among multiple species are limited. Methods: In this study, we compared the single-cell transcriptomes of 77 957 immune cells from 12 species using single-cell RNA-sequencing (scRNA-seq). Distinct molecular profiles were characterized for different immune cell types, including T cells, B cells, natural killer cells, monocytes, and dendritic cells. Results: The results revealed the heterogeneity and compositions of circulating immune cells among 12 different species. Additionally, we explored the conserved and divergent cellular cross-talks and genetic regulatory networks among vertebrate immune cells. Notably, the ligand and receptor pair VIM-CD44 was highly conserved among the immune cells. Conclusions: This study is the first to provide a comprehensive analysis of the cross-species single-cell atlas for peripheral blood mononuclear cells (PBMCs). This research should advance our understanding of the cellular taxonomy and fundamental functions of PBMCs, with important implications in evolutionary biology, developmental biology, and immune system disorders


eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Prashant Rajbhandari ◽  
Douglas Arneson ◽  
Sydney K Hart ◽  
In Sook Ahn ◽  
Graciel Diamante ◽  
...  

Immune cells are vital constituents of the adipose microenvironment that influence both local and systemic lipid metabolism. Mice lacking IL10 have enhanced thermogenesis, but the roles of specific cell types in the metabolic response to IL10 remain to be defined. We demonstrate here that selective loss of IL10 receptor α in adipocytes recapitulates the beneficial effects of global IL10 deletion, and that local crosstalk between IL10-producing immune cells and adipocytes is a determinant of thermogenesis and systemic energy balance. Single Nuclei Adipocyte RNA-sequencing (SNAP-seq) of subcutaneous adipose tissue defined a metabolically-active mature adipocyte subtype characterized by robust expression of genes involved in thermogenesis whose transcriptome was selectively responsive to IL10Rα deletion. Furthermore, single-cell transcriptomic analysis of adipose stromal populations identified lymphocytes as a key source of IL10 production in response to thermogenic stimuli. These findings implicate adaptive immune cell-adipocyte communication in the maintenance of adipose subtype identity and function.


2020 ◽  
Vol 11 ◽  
Author(s):  
Tingting Guo ◽  
Weimin Li ◽  
Xuyu Cai

The recent technical and computational advances in single-cell sequencing technologies have significantly broaden our toolkit to study tumor microenvironment (TME) directly from human specimens. The TME is the complex and dynamic ecosystem composed of multiple cell types, including tumor cells, immune cells, stromal cells, endothelial cells, and other non-cellular components such as the extracellular matrix and secreted signaling molecules. The great success on immune checkpoint blockade therapy has highlighted the importance of TME on anti-tumor immunity and has made it a prime target for further immunotherapy strategies. Applications of single-cell transcriptomics on studying TME has yielded unprecedented resolution of the cellular and molecular complexity of the TME, accelerating our understanding of the heterogeneity, plasticity, and complex cross-interaction between different cell types within the TME. In this review, we discuss the recent advances by single-cell sequencing on understanding the diversity of TME and its functional impact on tumor progression and immunotherapy response driven by single-cell sequencing. We primarily focus on the major immune cell types infiltrated in the human TME, including T cells, dendritic cells, and macrophages. We further discuss the limitations of the existing methodologies and the prospects on future studies utilizing single-cell multi-omics technologies. Since immune cells undergo continuous activation and differentiation within the TME in response to various environmental cues, we highlight the importance of integrating multimodal datasets to enable retrospective lineage tracing and epigenetic profiling of the tumor infiltrating immune cells. These novel technologies enable better characterization of the developmental lineages and differentiation states that are critical for the understanding of the underlying mechanisms driving the functional diversity of immune cells within the TME. We envision that with the continued accumulation of single-cell omics datasets, single-cell sequencing will become an indispensable aspect of the immune-oncology experimental toolkit. It will continue to drive the scientific innovations in precision immunotherapy and will be ultimately adopted by routine clinical practice in the foreseeable future.


2020 ◽  
Author(s):  
Xuan Liu ◽  
Sara J.C. Gosline ◽  
Lance T. Pflieger ◽  
Pierre Wallet ◽  
Archana Iyer ◽  
...  

AbstractSingle-cell RNA sequencing is an emerging strategy for characterizing the immune cell population in diverse environments including blood, tumor or healthy tissues. While this has traditionally been done with flow or mass cytometry targeting protein expression, scRNA-Seq has several established and potential advantages in that it can profile immune cells and non-immune cells (e.g. cancer cells) in the same sample, identify cell types that lack precise markers for flow cytometry, or identify a potentially larger number of immune cell types and activation states than is achievable in a single flow assay. However, scRNA-Seq is currently limited due to the need to identify the types of each immune cell from its transcriptional profile, which is not only time-consuming but also requires a significant knowledge of immunology. While recently developed algorithms accurately annotate coarse cell types (e.g. T cells vs macrophages), making fine distinctions has turned out to be a difficult challenge. To address this, we developed a machine learning classifier called ImmClassifier that leverages a hierarchical ontology of cell type. We demonstrate that ImmClassifier outperforms other tools (+20% recall, +14% precision) in distinguishing fine-grained cell types (e.g. CD8+ effector memory T cells) with comparable performance on coarse ones. Thus, ImmClassifier can be used to explore more deeply the heterogeneity of the immune system in scRNA-Seq experiments.


2021 ◽  
Author(s):  
Lauren E Fuess ◽  
Daniel I Bolnick

Pathogenic infection is an important driver of many ecological processes. Furthermore, variability in immune function is an important driver of differential infection outcomes. New evidence would suggest that immune variation extends to broad cellular structure of immune systems. However, variability at such broad levels is traditionally difficult to detect in non-model systems. Here we leverage single cell transcriptomic approaches to document signatures of microevolution of immune system structure in a natural system, the three-spined stickleback (Gasterosteus aculeatus). We sampled nine adult fish from three populations with variability in resistance to a cestode parasite, Schistocephalus solidus, to create the first comprehensive immune cell atlas for G. aculeatus. Eight major immune cell types, corresponding to major vertebrate immune cells, were identified. We were also able to document significant variation in both abundance and expression profiles of the individual immune cell types, among the three populations of fish. This variability may contribute to observed variability in parasite susceptibility. Finally, we demonstrate that identified cell type markers can be used to reinterpret traditional transcriptomic data. Combined our study demonstrates the power of single cell sequencing to not only document evolutionary phenomena (i.e. microevolution of immune cells), but also increase the power of traditional transcriptomic datasets.


2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yaning Li ◽  
Yan Wang ◽  
Yang Yao ◽  
Brian B. Griffiths ◽  
Liangshu Feng ◽  
...  

Stroke induces a robust inflammatory response. However, it still lacks a systematic view of the various immune cell types due to the limited numbers of fluorophore used in the traditional FACS technique. In our current study, we utilized the novel technique mass cytometry (CyTOF) to analyze multiple immune cell types. We detected these immune cells from the ischemic brain, peripheral blood, spleen, and bone marrow at different time courses after stroke. Our data showed (1) dynamic changes in the immune cell numbers in the ischemic brain and peripheral organs. (2) The expression levels of cell surface markers indicate the inflammation response status after stroke. Interestingly, CD62L, a key adhesion molecule, regulates the migration of leukocytes from blood vessels into secondary lymphoid tissues and peripheral tissues. (3) A strong leukocyte network across the brain and peripheral immune organs was identified using the R program at day 1 after ischemia, suggesting that the peripheral immune cells dramatically migrated into the ischemic areas after stroke. This study provides a systematic, wide view of the immune components in the brain and peripheral organs for a deep understanding of the immune response after ischemic stroke.


2017 ◽  
Vol 27 (3) ◽  
pp. 451-461 ◽  
Author(s):  
Santiago J. Carmona ◽  
Sarah A. Teichmann ◽  
Lauren Ferreira ◽  
Iain C. Macaulay ◽  
Michael J.T. Stubbington ◽  
...  

2019 ◽  
Author(s):  
Prashant Rajbhandari ◽  
Douglas Arneson ◽  
An-Chieh Feng ◽  
In Sook Ahn ◽  
Graciel Diamante ◽  
...  

SummaryImmune cells are vital constituents of the adipose microenvironment that influence both local and systemic lipid metabolism. Mice lacking IL10 have enhanced thermogenesis, but the roles of specific cell types in the metabolic response to IL10 remain to be defined. We demonstrate here that selective loss of IL10 receptor α in adipocytes recapitulates the beneficial effects of global IL10 deletion, and that local crosstalk between IL10-producing immune cells and adipocytes is a determinant of thermogenesis and systemic energy balance. Single Nuclei Adipocyte RNA-sequencing (SNAP-seq) of subcutaneous adipose tissue defined a metabolically-active mature adipocyte subtype characterized by robust expression of genes involved in thermogenesis whose transcriptome was selectively responsive to IL10Rα deletion. Furthermore, single-cell transcriptomic analysis of adipose stromal populations identified lymphocytes as a key source of IL10 production in response to thermogenic stimuli. These findings implicate adaptive immune cell-adipocyte communication in the maintenance of adipose subtype identity and function.


2022 ◽  
Vol 12 ◽  
Author(s):  
Daniel G. Bunis ◽  
Wanxin Wang ◽  
Júlia Vallvé-Juanico ◽  
Sahar Houshdaran ◽  
Sushmita Sen ◽  
...  

The uterine lining (endometrium) exhibits a pro-inflammatory phenotype in women with endometriosis, resulting in pain, infertility, and poor pregnancy outcomes. The full complement of cell types contributing to this phenotype has yet to be identified, as most studies have focused on bulk tissue or select cell populations. Herein, through integrating whole-tissue deconvolution and single-cell RNAseq, we comprehensively characterized immune and nonimmune cell types in the endometrium of women with or without disease and their dynamic changes across the menstrual cycle. We designed metrics to evaluate specificity of deconvolution signatures that resulted in single-cell identification of 13 novel signatures for immune cell subtypes in healthy endometrium. Guided by statistical metrics, we identified contributions of endometrial epithelial, endothelial, plasmacytoid dendritic cells, classical dendritic cells, monocytes, macrophages, and granulocytes to the endometrial pro-inflammatory phenotype, underscoring roles for nonimmune as well as immune cells to the dysfunctionality of this tissue.


Author(s):  
Xianwen Ren ◽  
Wen Wen ◽  
Xiaoying Fan ◽  
Wenhong Hou ◽  
Bin Su ◽  
...  

SUMMARYDysfunctional immune response in the COVID-19 patients is a recurrent theme impacting symptoms and mortality, yet the detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 205 COVID-19 patients and controls to create a comprehensive immune landscape. Lymphopenia and active T and B cell responses were found to coexist and associated with age, sex and their interactions with COVID-19. Diverse epithelial and immune cell types were observed to be virus-positive and showed dramatic transcriptomic changes. Elevation of ANXA1 and S100A9 in virus-positive squamous epithelial cells may enable the initiation of neutrophil and macrophage responses via the ANXA1-FPR1 and S100A8/9-TLR4 axes. Systemic upregulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis and designing effective therapeutic strategies for COVID-19.HIGHLIGHTSLarge-scale scRNA-seq analysis depicts the immune landscape of COVID-19Lymphopenia and active T and B cell responses coexist and are shaped by age and sexSARS-CoV-2 infects diverse epithelial and immune cells, inducing distinct responsesCytokine storms with systemic S100A8/A9 are associated with COVID-19 severity


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