Traditional second-generation sequencing examines the genome of a cell population, such as cell culture, tissue, organ, or entire organism. Its output is the "average genome" of the cell population, while single cell sequencing measures the genome of a single cell in the cell population . Nowadays, traditional methods are referred to as batch sequencing to distinguish them from single cell technology.Currently, single cell sequencing technology can be used to measure the genome (scDNA seq), DNA methylome, or transcriptome (scRNA seq) of each cell in a population.These technologies have been used to identify new mutations in cancer cells, explore progressive epigenomic changes that occur during embryonic development, and evaluate how a seemingly homogeneous cell population expresses specific genes.
Introduction To Single Cell Sequencing Technology
In single cell analysis methods, scRNA seq comprehensively measured the transcriptional expression of large volume cells. And quantitatively analyze all transcripts expressed in a single cell, providing an unbiased strategy to identify and describe the steps of analyzing organ rejection reactions in different cell populations using scRNA sequences. After transplantation tissue biopsy, cells are isolated and can be used for droplet or plate based sequencing methods. After batch effect correction, standardization, data imputation, and dimensional adjustment, specific cell subtypes can be determined. Heterogeneity analysis and tolerance prediction are used to determine target genes and molecular interactions, which are the foundation of gene therapy methods and long-term graft acceptance. Quality control; Dendritic cells.
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Application Of Single Cell Sequencing In Transplantation
At present, the main difficulties in successful transplantation include selecting the best matching donor and reducing lifelong immune suppression. For transplant rejection, the latest progress in scRNA seq provides an opportunity to fully reveal new cell types and states without result bias and RNA degradation A snapshot of the single-cell transcriptome shows different stages of immune differentiation and activation, which are rarely synchronized between cells. At single-cell resolution, it can describe immune cells, stromal cells, and new cell subtypes that suffer immune rejection, and further compare the unique characteristics of signaling pathways between different cell subpopulations. Here, we describe the effects of Scana-SEQ on the kidneys, liver, and liver, Advantages in the field of lung and hematopoietic stem cell (HSC) transplantation and immune applications.
T cells play a crucial role in transplant rejection. Most studies focus on bulk methods based on biopsy samples and do not provide information on t cell receptors (TCRs) αβ The lack of information on chain pairing may underestimate the actual differences in the library and cannot reflect that T cells with the same TCR can perform opposite biological functions. ScRNA seq technology overcomes the aforementioned limitations and makes library analysis more diverse.
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Kidney Transplantation
Liver Transplantation
The interaction between immune cells and liver cells in the transplantation environment is a key mechanism for inducing liver tolerance. SCRNA-seq can improve the liver immune cell map, explain the T cell subpopulations from other T cells in specific CD4+liver transplantation rejection and tolerance. Immune cells such as dendritic cells (DC), T cells, and NK cells may interact with sinusoidal endothelial cells and liver cells, adding specific signaling molecules to generate a tolerable state. Apoptosis of infiltrating T cells may be a key factor in allograft tolerance. Although tolerance induction may occur after liver transplantation, human allograft liver transplantation may still produce rejection reactions without the use of immunosuppressive drugs Approximately 10% -30% of allograft recipients are diagnosed with acute cellular rejection, possibly due to T cell related immune responses. The application of scRNA seq can better elucidate the cellular immune response in allograft liver transplantation.
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Lung Transplantation
The use of scRNA seq to detect single cells isolated from lung transplant donors and pulmonary fibrosis has revealed different populations of alveolar macrophage transcriptomes expressing pro fibrosis genes in patients with pulmonary fibrosis. It has been identified in Wnt/ β- Several mesenchymal cell markers that play a role in catenin signaling have been identified, and some previously described rare cell populations have been identified. These technologies can improve the diagnosis of fibrosis patients after lung transplantation and can be used to identify patients who are most likely to benefit from targeted treatment, During the progression of the disease, their responses were monitored [One hundred.]. mold et al. evaluated the cell population between healthy samples and found highly conserved cell heterogeneity in bronchoalveolar lavage (BAL) cells. By dynamically comparing the lungs of donors and recipients, persistent donor resident memory T cells were associated with better clinical outcomes, providing a potential therapeutic approach for extending the survival of allografts.
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Hematopoietic Stem Cell Transplantation
TCR-seq, as a type of scRNA seq, can clarify how acute GVHD occurs. Although the donor t-cell library has highly similar TCRs, the TCR library after HCT is very specific to the recipient. TCR recombination is highly random and may not rely on evaluating the most amplified TCR clones in a single receptor, but rather on complex polyclonal structures. These results can be used to guide clinical decision-making in preventing or treating acute graft-versus-host disease. By analyzing skin and peripheral blood T cells using TCR-seq, it was found that T cells on the host skin have unexpected pathogenic effects on graft-versus-host disease.
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Mmunological Application Of ScRNA Seq
ScRNA seq identifies the gene profiles of different cell populations. This technical tool avoids the drawbacks of batch analysis, which may miss out on cell specific features. It also improves understanding of immune cell ontogeny and stromal cell interactions in specific organs.
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