A theoretical framework of immune cell phenotypic classification and discovery

Immune cells are highly heterogeneous and show diverse phenotypes, but the underlying mechanism remains to be elucidated. In this study, we proposed a theoretical framework for immune cell phenotypic classification based on gene plasticity, which herein refers to expressional change or variability in response to conditions. The system contains two core points. One is that the functional subsets of immune cells can be further divided into subdivisions based on their highly plastic genes, and the other is that loss of phenotype accompanies gain of phenotype during phenotypic conversion. The first point suggests phenotypic stratification or layerability according to gene plasticity, while the second point reveals expressional compatibility and mutual exclusion during the change in gene plasticity states. Abundant transcriptome data analysis in this study from both microarray and RNA sequencing in human CD4 and CD8 single-positive T cells, B cells, natural killer cells and monocytes supports the logical rationality and generality, as well as expansibility, across immune cells. A collection of thousands of known immunophenotypes reported in the literature further supports that highly plastic genes play an important role in maintaining immune cell phenotypes and reveals that the current classification model is compatible with the traditionally defined functional subsets. The system provides a new perspective to understand the characteristics of dynamic, diversified immune cell phenotypes and intrinsic regulation in the immune system. Moreover, the current substantial results based on plasticitomics analysis of bulk and single-cell sequencing data provide a useful resource for big-data–driven experimental studies and knowledge discoveries

Discovery of novel human transcript variants by analysis of intronic single-block EST with polyadenylation site

Abstract Background Alternative polyadenylation sites within a gene can lead to alternative transcript variants. Although bioinformatic analysis has been conducted to detect polyadenylation sites using nucleic acid sequences (EST/mRNA) in the public databases, one special type, single-block EST is much less emphasized. This bias leaves a large space to discover novel transcript variants. Results In the present study, we identified novel transcript variants in the human genome by detecting intronic polyadenylation sites. Poly(A/T)-tailed ESTs were obtained from single-block ESTs and clustered into 10,844 groups standing for 5,670 genes. Most sites were not found in other alternative splicing databases. To verify that these sites are from expressed transcripts, we analyzed the supporting EST number of each site, blasted representative ESTs against known mRNA sequences, traced terminal sequences from cDNA clones, and compared with the data of Affymetrix tiling array. These analyses confirmed about 84% (9,118/10,844) of the novel alternative transcripts, especially, 33% (3,575/10,844) of the transcripts from 2,704 genes were taken as high-reliability. Additionally, RT-PCR confirmed 38% (10/26) of predicted novel transcript variants. Conclusion Our results provide evidence for novel transcript variants with intronic poly(A) sites. The expression of these novel variants was confirmed with computational and experimental tools. Our data provide a genome-wide resource for identification of novel human transcript variants with intronic polyadenylation sites, and offer a new view into the mystery of the human transcriptome.</p

Discovery of novel human transcript variants by analysis of intronic single-block EST with polyadenylation site

BACKGROUND: Alternative polyadenylation sites within a gene can lead to alternative transcript variants. Although bioinformatic analysis has been conducted to detect polyadenylation sites using nucleic acid sequences (EST/mRNA) in the public databases, one special type, single-block EST is much less emphasized. This bias leaves a large space to discover novel transcript variants. RESULTS: In the present study, we identified novel transcript variants in the human genome by detecting intronic polyadenylation sites. Poly(A/T)-tailed ESTs were obtained from single-block ESTs and clustered into 10,844 groups standing for 5,670 genes. Most sites were not found in other alternative splicing databases. To verify that these sites are from expressed transcripts, we analyzed the supporting EST number of each site, blasted representative ESTs against known mRNA sequences, traced terminal sequences from cDNA clones, and compared with the data of Affymetrix tiling array. These analyses confirmed about 84% (9,118/10,844) of the novel alternative transcripts, especially, 33% (3,575/10,844) of the transcripts from 2,704 genes were taken as high-reliability. Additionally, RT-PCR confirmed 38% (10/26) of predicted novel transcript variants. CONCLUSION: Our results provide evidence for novel transcript variants with intronic poly(A) sites. The expression of these novel variants was confirmed with computational and experimental tools. Our data provide a genome-wide resource for identification of novel human transcript variants with intronic polyadenylation sites, and offer a new view into the mystery of the human transcriptome

Role of FABP5 in T Cell Lipid Metabolism and Function in the Tumor Microenvironment

To evade immune surveillance, tumors develop a hostile microenvironment that inhibits anti-tumor immunity. Recent immunotherapy breakthroughs that target the reinvigoration of tumor-infiltrating T lymphocytes (TIL) have led to unprecedented success in treating some cancers that are resistant to conventional therapy, suggesting that T cells play a pivotal role in anti-tumor immunity. In the hostile tumor microenvironment (TME), activated T cells are known to mainly rely on aerobic glycolysis to facilitate their proliferation and anti-tumor function. However, TILs usually exhibit an exhausted phenotype and impaired anti-tumor activity due to the limited availability of key nutrients (e.g., glucose) in the TME. Given that different T cell subsets have unique metabolic pathways which determine their effector function, this review introduces our current understanding of T cell development, activation signals and metabolic pathways. Moreover, emerging evidence suggests that fatty acid binding protein 5 (FABP5) expression in T cells regulates T cell lipid metabolism and function. We highlight how FABP5 regulates fatty acid uptake and oxidation, thus shaping the survival and function of different T cell subsets in the TME

Analysis of TCR Repertoire by High-Throughput Sequencing Indicates the Feature of T Cell Immune Response after SARS-CoV-2 Infection

Coronavirus disease 2019 (COVID-19) is a global infectious disease caused by the SARS-CoV-2 coronavirus. T cells play an essential role in the body’s fighting against the virus invasion, and the T cell receptor (TCR) is crucial in T cell-mediated virus recognition and clearance. However, little has been known about the features of T cell response in convalescent COVID-19 patients. In this study, using 5′RACE technology and PacBio sequencing, we analyzed the TCR repertoire of COVID-19 patients after recovery for 2 weeks and 6 months compared with the healthy donors. The TCR clustering and CDR3 annotation were exploited to discover groups of patient-specific TCR clonotypes with potential SARS-CoV-2 antigen specificities. We first identified CD4+ and CD8+ T cell clones with certain clonal expansion after infection, and then observed the preferential recombination usage of V(D) J gene segments in CD4+ and CD8+ T cells of COVID-19 patients with different convalescent stages. More important, the TRBV6-5-TRBD2-TRBJ2-7 combination with high frequency was shared between CD4+ T and CD8+ T cells of different COVID-19 patients. Finally, we found the dominant characteristic motifs of the CDR3 sequence between recovered COVID-19 and healthy control. Our study provides novel insights on TCR in COVID-19 with different convalescent phases, contributing to our understanding of the immune response induced by SARS-CoV-2

Co-Expression with Membrane CMTM6/4 on Tumor Epithelium Enhances the Prediction Value of PD-L1 on Anti-PD-1/L1 Therapeutic Efficacy in Gastric Adenocarcinoma

Anti-PD-1/L1 immunotherapy has been intensively used in heavily treated population with advanced gastric adenocarcinoma. However, the immunotherapeutic efficacy is low even in PD-L1 positive patients. We aimed to establish a new strategy based on the co-expression of CMTM6/4 and PD-L1 for patient stratification before immunotherapy. By analyzing the data obtained from TCGA and single-cell RNA sequencing at the mRNA level, and 6-color multiplex immunofluorescence staining of tumor tissues in tissue array and 48-case pre-immunotherapy patients at the protein level, we found that CMTM6/4 and PD-L1 co-expressed in both epithelial and mesenchymal regions of gastric adenocarcinoma. The tumor tissues had higher levels of CMTM6/4 expression than their adjacent ones. A positive correlation was found between the expression of CMTM6/4 and the expression of PD-L1 in tumor epithelium. Epithelial co-expression of CMTM6/4 and PD-L1 in gastric tumor region was associated with shorter overall survival but better short-term response to anti-PD-1/L1 immunotherapy. Thus, we developed a predictive model and three pathological patterns based on the membrane co-expression of CMTM6/4 and PD-L1 in tumor epithelial cells for pre-immunotherapy patient screening in gastric adenocarcinoma