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A Thousand Color FACS Analysis – Single Cell Sequencing in Immunology
Time:2022-03-23 23:32:57  

The immune system comprises a network of cells that not only mediate the defense against pathogens and diseases like cancer, but also play a critical role in homeostasis such as tissue development and metabolism [1,2]. Until recently, in order to study the immune system, immunologists often relied on microscopy and flow cytometry methods to define cell types and sort them depending on their surface marker profiles. This was restricting due to the limit of simultaneous markers that can be fluorescently labelled and spectra overlap between them, which also limited the resolution of cell characterization, resulting in less cell subpopulations described and missing rare cells that might be important for biomarker and drug discovery.

 

Hight-throughput single cell sequencing defines cell populations based on the expression of thousands of genes in each individual cell and annotates clusters of these cells based on their characteristic gene expression patterns. This effectively increases the number of marker genes and can be described as “FACS with thousands of colors” to define each single cell. Such unprecedented high resolution of cellular analysis can be used to define new immune cell types and subtypes, understand the development trajectory of different cell types, and study the interaction of immune cells with each other, as well as other cells in different tissues.

 

The application of this technology in immunology provides answers to the questions that standard cell biology methods like FACS or bulk sequencing fail to address, such as resolving immune cell heterogeneity, revealing gene expression and pathway regulations upon infection or disease, pinpointing B-cells and T-cells going through expansion, mapping the crosstalk between the immune system and disease environment, characterizing treatment response and the cell populations involved, rare cell type and biomarker discovery, etc [3,4,5]. This opens the door for deeper insights into the development of immune cells, mechanisms and potential treatment of autoimmune diseases and hematologic cancers, and the possibility of modulating the immune system to fight off various diseases. Here we show how Singleron’s single cell RNA library preparation and other products enabled researchers to study autoimmune diseases, manage organ transplantation and surgery outcomes, study diabetic immune states, design and optimize cancer immunotherapy, link the host-parasite immune cell interactions, and mine public databases to study immune cell senescence.

 

 

Autoimmune Diseases

 

Autoimmune diseases occur when the immune system is activated against the body’s own proteins, resulting in damage to self-tissues and organs. Single cell sequencing can identify new immune cell subpopulations related to diseases at the single cell level, determine gene expression heterogeneity, and explore the differentiation and developmental properties of immune cells, thus providing a new method for research on the pathogenesis and treatment of autoimmune diseases. Understanding the role of each cell population involved during an autoimmune reaction is crucial to treatment development. Tang et al. performed single cell RNA sequencing on kidney biopsies to study IgA nephropathy (IgAN), the most common glomerular disease worldwide which is also considered to be an autoimmune disease [6]. Researchers found that FCGBP, a negative regulator of Epithelial to Mesenchymal Transition (EMT), which is proved to have the function of cell protection and anti-inflammation in tissues, was under-expressed in macrophages from kidney of IgAN patients. This approach defined the macrophages as the most relevant population from dozens of cell types in the biopsy analysis, which contrasts with FACS analysis that would require sorting of specific, preselected target populations to tests individually, which not only drastically saves time and costs, but also provides much deeper insight into the pathology of the disease.

 

Immune Interactome Mapping

 

Assembly of the cell interactome within a particular tissue or organ allows the study of crosstalk between immune cells and the disease environment. Xu et al. applied single cell RNA sequencing to kidney biopsies of patients with Idiopathic Membranous Nephropathy (IMN), a noninflammatory autoimmune disease of the kidney glomerulus, to identify gene expression at the single-cell level, elucidate cells involved in the progression of IMN, and uncover intercellular interactions [7]. Gene expression and pathway enrichment analyses showed that macrophages highly expressed genes responsible for the regulation of leukocyte activation (AXL) inflammatory response (CXCR4), and the antigen processing and presentation, as well as immune response-regulating signaling pathway (HLA-DPA1). Ligand-receptor analysis implicated mesangial and endothelial cells in neutrophil/macrophage infiltration and inflammation response via CCL2 and ACKR1 interaction. Macrophages highly expressed PTGER4, a receptor previously described as a driver for differentiation of Th1 cells and proliferation of Th17 cells, which are key players in kidney autoimmunity. This approach characterized putative novel therapeutic targets for IMN by profiling kidney interactome.

 

 

 

 

Organ Transplantation

 

In some cases, the disease progression results in irreparable damage to the organ and transplantation is the only treatment option.  Renal transplantation is currently the most effective treatment for end-stage renal disease. However, chronic antibody-mediated rejection (cABMR) remains a serious obstacle for the long-term survival of patients with renal transplantation. Kong et al. defined the transcriptomic landscape of PBMCs in patients after renal transplantation at single-cell resolution [8]. They found that the expression of pro-inflammatory response and immune regulation genes (MTND6, CXCL8, NFKBIA) were up-regulated in γδT cells, CD8 effector T cells, and CD8_MAI T cells. Also, enrichment analysis confirmed that both NF-kB and MAPK signaling pathways were involved in the activation of T-cells and antibody-mediated rejection. Lastly, the interactome analysis revealed that T- and B- cells are responsible for neutrophil activation through the CXCL8-CXCR1/2 signaling axis. Such transcriptomics data provides detailed cell lineage and interaction information and can serve as a rich resource for a detailed understanding of peripheral lymphocytes in patients with cABMR.

 

 

 

Surgical Procedures

 

Surgery in organ transplantation is not the only type of surgical procedures where immunological studies are of paramount importance in improving patient recovery. Takayasu Arteritis (TA) is a highly specific vascular autoimmune disease driven by IL6-mediated differentiation of CD4+ T-cells into tH17 cells, resulting in interleukin release and chronic inflammation of arteries. Although they had accepted medical treatment, some patients’ lesions still require surgical management. Qing et al. aimed at dissecting the transcriptomes of PBMCs in these patients and to explore potential clinical markers for TA development and progression [9]. They found that the proportion of CD14+ monocytes is higher in TA patients which suppresses CD4+ function and increases inflammation. Also, they discovered that TXNIP and AREG can be used as new diagnostic markers for TA development and progression. Taken together, they suggested the inhibition of monocytes as a novel direction in medical treatment of TA.

 

 

 

Biomaterials in Surgery

 

In some cases, surgery requires additional biomaterials for the success of the procedure and patient recovery with minimal risk of rejection or tearing. Postoperative anastomotic leakage (PAL) is a “nightmare scenario” for patients and surgeons after gastrointestinal surgery. More than half of the patients do not benefit from currently available interventions, such as improved surgical technology, preoperative mechanical bowel preparation and oral antibiotics. Molecular mimicry can be utilized to engineer molecules that share structural and functional similarities to the originals. Huang et al. developed a novel marine-inspired hydrogel adhesive based on dopamine-conjugated xanthan gum and tested its degradability, self-healing, injectability, and strong adhesive strength [10]. They showed that released Da-g-Xan regulates the inflammatory status of macrophages and reverses cell phenotypes from M1 to M2, which improved their paracrine action and intensified diverse functions of fibroblasts. In conclusion, Da-g-Xan hydrogel adhesive induces M2 macrophages in vivo and protects surgical anastomosis through improving vascularization and collagen deposition.

 

 

 

Type 1 Diabetes (T1D)

 

Diabetes is another multifactorial autoimmune disease for which a broad knowledge of the genetics, epidemiology, and clinical management has been achieved. However, information about the cell heterogeneity in the bone marrow during Type 1 Diabetes remained scarce due to the limits of available technologies. Zhong et al. used single cell sequencing to present a profile of the bone marrow cells and reveal the relationship of bone marrow and osteopenia in streptozotocin (STZ)-induced T1D mice [11]. They revealed that the proportion of BM-neutrophils significantly increased while the proportion of B lymphocytes significantly decreased in T1D samples, which also negatively correlated with osteopenia in STZ-induced T1D mice. Sigle cell sequencing technology was capable of shedding light on the heterogeneity of cells in the bone marrow and link their transcriptome and differentiation patterns to their overall role in the diabetic disease milieu.

 

 

 

Immunotherapy in Cancer

 

Immunotherapy is an effective avenue for countering immune checkpoints established in some types of cancer. Osteosarcoma (OS) is a highly aggressive malignant bone tumor frequently occurring in children and adolescents. The anti-PD-L1 treatment only has a limited therapeutic effect on OS, highlighting the urgent need to understand the molecular mechanisms underlying the OS development and progression. Zhou et al. used single cell sequencing to characterize the transcriptomic properties, regulators, and dynamics of osteosarcoma malignant cells together with their tumor microenvironment, particularly stromal and immune cell [12]. They discovered that CD8+ T, CD4+ T, regulatory T (T-reg), and NKT cells in OS lesions highly expressed immunoreceptor inhibitory checkpoint marker TIGIT (T cell Immunoreceptor with Ig and ITIM domains). Furthermore, they showed that TIGIT blockade enhanced the cytotoxicity effects of the primary CD3+ T cells with high proportion of TIGIT+ cells against osteosarcoma. These results presented a single-cell atlas, explored intratumor heterogeneity, and provided potential therapeutic targets for osteosarcoma.

 

 

 

Immune States During Parasitic Infestation

 

Altered immune status can also be the effect of parasitic infestation as well as infection. Schistosomiasis is a widespread helminth disease that poses a heavy social and economic burden on people worldwide. Advanced schistosomiasis often develops into schistosome-associated liver fibrosis, the pathogenesis of which remains unclear. Zhang et al. aimed to profile immune cells of schistosome-associated liver fibrosis using single-cell RNA sequencing [13]. They showed that the numbers of T cell-1, mononuclear phagocytes (MP)-1, and dendritic cells (DCs) were increased in the infested liver. Moreover, they defined CAVIN2+ Kupffer cells as the main source of TGFB1, consisting primarily of mononuclear phagocytes and potentially playing an irreplaceable role in hepatic fibrosis of schistosomiasis. This is a great example of how single cell sequencing can profile the immune state of a disease-affected tissue and define the main cell subtypes involved in the pathogenesis.

 

 

 

Senescence of Immune Cells

Immune cell senescence studies are crucial to understand aging-related autoimmune states. During aging, bone homeostasis is typically disrupted, as characterized by low bone turnover and marrow fat accumulation that eventually results in osteoporosis and fragility related fracture. Proinflammatory and senescent subtypes of immune cells, including macrophages and neutrophils, accumulate in the bone marrow during aging in rats and mice and secrete abundant quantities of grancalcin (GCA) to induce an imbalance in osteogenesis versus adipogenesis of bone marrow stromal cells (BMSCs). Li et al. performed deep mining of the single cell sequencing database of bone marrow cells to characterize cells involved in GCA secretion and skeletal aging [14]. They concluded that young mice have more neutrophils and macrophages, with higher GCA levels produced by these cells than old mice, and that genetic deletion of Gca in neutrophils and monocytes-macrophages was sufficient to slow skeletal aging in mice. This study shows a great example of how mining single cell sequencing databases can give novel insights into the mechanisms of diseases and allow for more precise planning of future experimental designs with much lower costs and more relevant and specific subject niches.

 

 

A New Era in Clinical Translational Research

 

Single cell sequencing technology ushers the new era of clinical transcriptomics and multiomics in immunology, enabling high resolution mapping of cell subpopulations involved in diseases with highly heterogenous tissue content, as well as functionally linking them to other players within the disease environment. Studies of immune cell development and mechanisms of autoimmune diseases can also be based on in silico analysis via deep mining of single cell sequencing databases. In conclusion, scientists can focus on the most relevant cell types and their interaction partners and monitor treatment and surgical procedure success, as well as patient recovery. This includes profiling immunotherapy results and other immune states characterization with the goal of defining new biomarkers and therapeutic targets.

 

 

[1] Sabine Daemen and Joel D. Schilling. The interplay between tissue niche and macrophage cellular metabolism in obesity. Front. Immunol., 2019. [PubMed]

[2] Maxim N. Artyomov and Jan Van den Bossche. Immunometabolism in the single-cell era.. Cell Metab., 2020. [PubMed]

[3] Daniel et al. Single-cell mapping of progressive fetal-to-adult transition in human naive T cells. Cell Reports, 2021. [PubMed]

[4] Seungmae Seo and Emily M Mace. Diversity of human NK cell developmental pathways defined by single-cell analyses. Current Opinion in Immunology, 2022. [PubMed]

[5] Park et al. A cell atlas of human thymic development defines T cell repertoire formation. Science, 2020. [PubMed]

[6] Tang et al. A partial picture of the single-cell transcriptomics of human IgA nephropathy. Front. Immunol., 2021. [PubMed]

[7] Xu et al. Single-cell profiling reveals transcriptional signatures and cell-cell crosstalk in anti-PLA2R positive idiopathic membranous nephropathy patients. Front. Immunol., 2021. [PubMed]

[8] Kong et al. Single-cell transcriptome analysis of chronic antibody-mediated rejection after renal transplantation. Front. Immunol., 2022. [PubMed]

[9] Huang et al. Marine-inspired molecular mimicry generates a drug-free, but immunogenic hydrogel adhesive protecting surgical anastomosis. Bioactive Materials, 2021. [PubMed]

[10] Gao et al. Single-cell RNA sequencing revealed CD14+ monocytes increased in patients with Takayasu’s Arteritis requiring surgical management. Front Cell Dev Biol., 2021. [PubMed]

[11] Zhong et al. Single-cell RNA sequencing analysis reveals the relationship of bone marrow and osteopenia in STZ-induced type 1 diabetic mice..Journal of Advanced Research [PubMed]

[12] Zhang et al. Single-cell RNA landscape of intratumoral heterogeneity and immunosuppressive microenvironment in advanced osteosarcoma. Nature Communications, 2020. [PubMed]

[13] Zhang et al. A preliminary investigation into the immune cell landscape of schistosome-associated liver fibrosis in humans..Immunology & Cell Biology, 2021. [PubMed]

[14] Li et al. Senescent immune cells release grancalcin to promote skeletal aging. Cell Metabolism, 2021. [PubMed]

 

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