阅读说明：本技术 单细胞测序作为标志物在制备诊断原发性干燥综合征中的应用 (Application of single cell sequencing as marker in preparation of diagnosis of primary sicca syndrome ) 是由 万磊 刘健 黄传兵 谌曦 范海霞 葛瑶 刘天阳 刘磊 李明 赵磊 孙广瀚 朱子 于 2021-08-23 设计创作，主要内容包括：本发明提供了一种单细胞测序作为标志物在制备诊断原发性干燥综合征中的应用,单细胞测序通过流式活化细胞分离外周血单个核细胞得到,原发性干燥综合征中主要由NK细胞组成,其次为T细胞和B细胞。本发明的单细胞测序技术在单个细胞水平上对基因组、转录组、蛋白质组及表观基因组进行测序,能够从组织样本中获得不同细胞间的异质性信息,具备准确、高效、安全可靠的优点,从而在细胞层面筛选出干燥综合征的差异表达标志物,弥补干燥综合征诊断的不足；本发明的单细胞测序简便,不需特别准备、不需特定时间,随时随地均可采集标本。另外,其还有创伤性极小和敏感性高的优点。(The invention provides an application of single cell sequencing as a marker in preparation and diagnosis of primary sicca syndrome, wherein the single cell sequencing is obtained by separating peripheral blood mononuclear cells through flow activated cells, the primary sicca syndrome mainly comprises NK cells, and T cells and B cells are used in the secondary sicca syndrome. The single cell sequencing technology provided by the invention can sequence the genome, the transcriptome, the proteome and the epigenome on a single cell level, can obtain heterogeneity information among different cells from a tissue sample, and has the advantages of accuracy, high efficiency, safety and reliability, so that differential expression markers of sjogren's syndrome are screened out at a cell level, and the defect of diagnosis of sjogren's syndrome is made up; the single cell sequencing of the present invention is simple, needs no special preparation and no specific time, and can collect sample at all times and places. In addition, it has the advantages of minimal invasiveness and high sensitivity.)

1. Application of single cell sequencing as a marker in preparation of diagnosis of primary sicca syndrome.

2. Use according to claim 1, characterized in that: the single cell sequencing is obtained by separating peripheral blood mononuclear cells by flow activated cells.

3. Use according to claim 2, characterized in that: the peripheral blood mononuclear cells include B cells, NK cells, T cells, monocytes and platelet cells.

4. Use according to any one of claims 1 to 3, characterized in that: the primary sjogren's syndrome is mainly composed of NK cells.

5. Use according to any one of claims 1 to 3, characterized in that: the primary sjogren's syndrome also includes T cells and B cells.

Technical Field

The invention belongs to the technical field of biological detection, and particularly relates to application of single cell sequencing as a marker in preparation and diagnosis of primary sicca syndrome.

Background

The primary sicca syndrome (pSS) has a hidden onset, most patients have difficulty in clearly explaining the onset time, the clinical manifestations are various, multiple systems of the whole body can be involved, the disease condition varies greatly, and the treatment means is limited. pSS is a disease species which is easy to misdiagnose and neglect diagnosis, and the establishment of the diagnosis standard of pSS has 13 classification standards in the development and evolution process of over fifty years, but various dissatisfaction still exists in the clinical application up to now. pSS lacks a single and objective diagnostic index, and conventional diagnosis usually requires comprehensive analysis based on multiple indexes and classification criteria, including subjective symptoms and objective examination of salivary glands, eyes, serology, histopathology, and the like.

The measurement and evaluation of subjective symptoms have obvious individual and regional differences and poor specificity; individual differences in salivary flow rate are large, and there is no uniform collection method; the secretory functions of lacrimal glands can be evaluated by a Schirmer test, an eye staining score and a tear film rupture test, but parameters of the method have large difference in various standards, dry eye manifestations of pSS patients are large in difference, eyes of a part of pSS patients do not have obvious influence, so that the methods lack specificity, and result errors are large; autoantibodies, although of diagnostic importance, are negative for about one-third of patients, and the autoantibodies currently used in laboratory diagnosis-anti-SSA, anti-SSB, anti-M3, anti-cardiolipin and α -fibrin antibodies generally have the disadvantage of low specificity or sensitivity; the histopathological examination generally adopts the lip gland biopsy, but because the operation is invasive, the lip gland biopsy is unacceptable for patients, the clinical use rate is low, and the prognosis evaluation is not facilitated, so that the histopathological examination faces the dilemma that the wide implementation is difficult in the pathological diagnosis process. The diagnosis of pSS cannot be excluded due to negative examination of the specific autoantibody, the body and mind of a patient are greatly painful due to invasive operation of the labial gland biopsy, the labial gland biopsy is not widely applied to clinic, and the individual difference and the specificity are poor in the salivary gland and eye examination.

Multidisciplinary cooperation and examination of multiple taxonomic entries presents challenges to the diagnosis of pSS, resulting in a relative lag between diagnosis and treatment of the disease. Therefore, new diagnostic methods are urgently to be discovered, and methods for improving the diagnostic accuracy of pSS are urgently sought. Single Cell Sequencing (SCS) technology has great potential in early diagnosis, development and prognosis evaluation of pSS. At present, a single cell sequencing method is not applied to diagnosis of sjogren's syndrome.

Disclosure of Invention

Aiming at the defects in the prior art, the invention aims to provide the application of single cell sequencing as a marker in the preparation of a diagnostic primary sicca syndrome

In order to achieve the above purpose, the solution of the invention is as follows:

application of single cell sequencing as a marker in preparation of diagnosis of primary sicca syndrome.

Preferably, single cell sequencing is obtained by flow activated cell isolation of peripheral blood mononuclear cells.

Preferably, peripheral blood mononuclear cells include B cells, NK cells, T cells, monocytes and platelet cells.

Preferably, primary sjogren's syndrome consists essentially of NK cells.

Preferably, primary sjogren's syndrome also includes T cells and B cells.

Due to the adoption of the scheme, the invention has the beneficial effects that:

firstly, the single cell sequencing technology provided by the invention can sequence genomes, transcriptomes, proteomes and epigenomes on a single cell level, can obtain heterogeneity information among different cells from a tissue sample, and has the advantages of accuracy, high efficiency, safety and reliability, so that differential expression markers of sjogren's syndrome are screened out at a cell level, and the defect of diagnosis of sjogren's syndrome is made up.

Secondly, the single cell sequencing of the invention is simple and convenient, does not need special preparation and special time, and can collect samples at any time and any place.

Thirdly, the unicellular sequencing technology of the invention has extremely small wound, and the detection only needs to draw about 3mL of blood by common vein blood drawing, is a non-invasive new detection, is different from the xerosis syndrome labial gland biopsy technology (the invasive operation brings great pain to the mind and body of the patient), and reduces the pain of the patient.

Fourth, the invention has high sensitivity, and can detect patients with sjogren's syndrome at an early stage, and the abnormal concentration of a plurality of markers is usually earlier than the abnormal concentration of autoantibodies, even earlier than the abnormal typical symptoms of dry mouth and dry eyes.

Drawings

FIG. 1 is a schematic diagram of UMAP cluster visualization of Controls (CN) and primary sjogren syndrome patients (pSS) according to the present invention.

FIG. 2 is a cell type map of sequenced PBMCs in CN and pSS of the present invention.

FIG. 3 is a schematic representation of the cellular expression of PBMCs in CN and pSS of the present invention.

FIG. 4 is a schematic representation of T cell subsets in CN and pSS of the invention.

FIG. 5 is a graph of the expression process of different cells in a T cell subpopulation of the present invention.

FIG. 6 is a graph of the content of different T cell subtypes of the present invention during pSS.

Detailed Description

The invention provides an application of single cell sequencing as a marker in preparation of a diagnostic primary sicca syndrome.

Peripheral Blood Mononuclear Cells (PBMCs) were isolated from control group (CN) and active primary sicca syndrome (pSS) and single cell RNA sequencing (scra-seq) was performed using 10x genomics platform. Cells were unsupervised clustered based on gene expression profiles using the saurat package and passed to UMAP for cluster visualization (see figure 1).

In particular, the amount of the solvent to be used,

1. single cell RNA sequence workflow

PBMCs are isolated from whole blood. Performing single-cell complete transcriptome analysis based on a BD-Rhapscody system complete transcriptome analysis alpha protocol, and constructing the captured single-cell transcriptome microbeads into a cDNA library containing cell tags and UMI information. Briefly, double-stranded cDNA is first extracted from a captured single-cell transcript, subjected to reverse transcription, second strand synthesis, end preparation, ligation adapter, and whole-transcript amplification. Random primer amplification was performed using a BD-Rhapbody-cDNA kit (BD-Biosciences, 633773) and a BD-Rhapbody-Targeted-mRNA & AbSeq amplification kit (BD-Biosciences, 633774) to obtain a final cDNA library. The library was sequenced in PE150 mode on a NovaSeq instrument (Illumina) (reading the opposite end of 150 bp).

2. Single cell data preprocessing, gene expression quantification and cell type determination

Raw reads were processed through a BD-Rhapsody whole transcriptome analysis pipeline (Early access) including filtering by read quality, annotation reading, annotation of molecules, determination of putative cells and generation of single cell expression matrices. Briefly, in the read quality filtering step, read pairs with low sequencing quality (too long, too short, low sequencing score, or high single nucleotide frequency) are first removed. The selected R1 reads were analyzed to identify the cell tag sequence (CL), the molecular recognition sequence (UMI) and the poly-dT tail sequence, while the selected R2 reads were mapped to the ensembl hg19 using STAR (verison 2.5.2b) [1] in the read annotation step. Artifact molecules due to magnification variation in the molecular annotation step are further corrected using Recursive Substitution Error Correction (RSEC) and distribution-based error correction (DBEC) algorithms. In the putative cell determination step, the putative cells are distinguished from background noise using second derivative analysis. Finally, putative cellular information was combined with RSEC/DBEC regulatory molecules to generate single cell expression matrices. The pipeline outputs provide raw gene expression matrices corrected by RSEC and DBEC algorithms. In all matrices, UMI counts per cell corrected with DBEC algorithm were used for cluster analysis. The original gene expression matrices from both cassettes were read into R separately (version 3.6.0) and the Seurat R package (version 3.0.1) [2] was used. It is converted into a securat object. CCA integration was performed between batches using the securat R package. A total of 21373 cells were obtained from both groups of samples for further analysis. The gene expression matrix was then normalized to total cell UMI counts. The first 2000 features were selected as high-variant genes for cluster analysis. After scaling the data according to the UMI counts, PCA was performed to reduce dimensionality based on the highly variable genes determined in the previous step. On the basis, the first 50 principal components are selected according to a pcheat diagram, a Jackstraw diagram and a pcelbow diagram, and the dimensionality is further reduced by using a tSNE algorithm. Clusters are identified with default settings using the RunTSNE function. Each cluster is then annotated with canonical cluster labels. The MSigDB hallmark gene set in the GSVA R package [3] was used for GSEA analysis [4 ]. Single cell preparation, library construction and sequencing were performed by Aoji Biotechnology, Inc., Shanghai.

As a result:

scRNA sequence revealing novel cell type markers in PMBC

PBMC suspensions were first isolated and sequenced from two cell pools of CN and pSS. 11792 PBMCs were sequenced and after rejecting non-target cells that could represent duplexes, empty droplets, low quality cells and platelets, 6929 PBMCs were further analyzed, of which 1433 cells from healthy control humans and 5496 cells from pSS. Unsupervised clustering using the saurta software package identified 21 different cell clusters and 5 types of cells in both groups, 5 types of cells being B cells, NK cells (Myeloid), T cells, monocytes, Platelet cells (Platelet), respectively (fig. 2). B cells (approximately 12.1% of all cells), NK cells (approximately 17.8% of all cells) expressed CD79A predominantly, T cells (approximately 21.5% of all cells) expressed CD3E predominantly, monocytes (approximately 48.3% of all cells) expressed CD14 predominantly, and platelet cells expressed PF4 predominantly. (FIG. 3). The scRNA sequences indicated that PBMCs isolated from CN consisted primarily of T cells (about 51.2%), followed by myeloid cells (about 31.8%) and B cells (about 17.0%). In contrast, pSS has a higher frequency of myeloid cells (-53.0%) and lower frequencies of T cells (-36.4%) and B cells (-10.9%) compared to CN.

Characterization of T cell subsets by scRNA-seq, revealing features of T cell subset distribution in pSS

The scRNA-seq analysis detected 2715T cells in all two donor groups. On pSS PBMCs, T cells can regulate 185 genes, including 113 up-regulated genes and 72 down-regulated genes. The down-regulated genes at the first 4 position are metallothionein and comprise MT2A, MT1X, MT1E and MT1F, and the up-regulated genes at the first 4 position are SKIL, BTN3A2, GZMH and SSBP 3.

2715T cells were divided into 14 subsets (fig. 4). 13 of the 14 subsets expressed high levels of CD3 (including CD3D, CD3E, and CD 3G). 4 different CD4+ T cell subsets: 0.1, 2 and 11. 8 different CD8+ T cell subsets were identified: 4. 5, 6, 7, 9, 12, 13 and 14. As shown in fig. 5, T0 expresses high levels of CD4+ T cell markers and functional markers, such as TCF7, which regulate T cell trafficking and migration. Cluster 8 and cluster 11 highly express KLRD1, NKG7, etc., and they express NK cells.

To further observe the role of different T cell subtypes in the pSS process, T cells were further sub-analyzed and 5T cell subtypes were identified (fig. 6). The 5T cell subtypes are identified as CD4+ naive T cells, CD8+ naive T cells, CD8+ effector T cells, NK cells and proliferative T cells. Compared with the T cell subtype distribution of the pSS group and the control group, the content of the juvenile CD8+ T cells in the pSS group is obviously reduced, the content of effector T cells is obviously increased, and the inflammatory state can cause the functional activation of CD8+ T cells.

Reference documents:

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[2].Butler A,Hoffman P,Smibert P,Papalexi E,Satija R:Integrating single-cell transcriptomic data across different conditions,technologies,and species.Nature Biotechnology 2018,36(5)：411-420.

[3].S,Castelo R Fau-Guinney J,Guinney J:GSVA:gene set variation analysis for microarray and RNA-seq data.BMC Bioinformatics,2013,14:7(1471-2105-14-7.).

[4].Liberzon A,Birger C,Thorvaldsdóttir H,Ghandi M,Mesirov J,Tamayo P:The Molecular Signatures Database(MSigDB)hallmark gene set collection.Cell Syst 2015,1(6):417-425.

finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that various changes, modifications and substitutions can be made without departing from the spirit and scope of the invention as defined by the appended claims. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.