Single-cell RNA sequencing unveils the hidden powers of zebrafish kidney for generating both hematopoiesis and adaptive antiviral immunity.

The vertebrate kidneys play two evolutionary conserved roles in waste excretion and osmoregulation. Besides, the kidney of fish is considered as a functional ortholog of mammalian bone marrow that serves as a hematopoietic hub for generating blood cell lineages and immunological responses. However, knowledge about the properties of kidney hematopoietic cells, and the functionality of the kidney in fish immune systems remains to be elucidated. To this end, our present study generated a comprehensive atlas with 59 hematopoietic stem/progenitor cell (HSPC) and immune-cells types from zebrafish kidneys via single-cell transcriptome profiling analysis. These populations included almost all known cells associated with innate and adaptive immunity, and displayed differential responses to viral infection, indicating their diverse functional roles in antiviral immunity. Remarkably, HSPCs were found to have extensive reactivities to viral infection, and the trained immunity can be effectively induced in certain HSPCs. In addition, the antigen-stimulated adaptive immunity can be fully generated in the kidney, suggesting the kidney acts as a secondary lymphoid organ. These results indicated that the fish kidney is a dual-functional entity with functionalities of both primary and secondary lymphoid organs. Our findings illustrated the unique features of fish immune systems, and highlighted the multifaced biology of kidneys in ancient vertebrates.

Dynamics of Whole Transcriptome Analysis (WTA) and Surface markers expression (AbSeq) in Immune Cells of COVID-19 Patients and Recovered captured through Single Cell Genomics.

Introduction: Single-cell multi-omics studies, such as multidimensional transcriptomics (whole transcriptomic analysis, WTA), and surface marker analysis (antibody sequencing, AbSeq), have turned out to be valuable techniques that offer inaccessible possibilities for single-cell profiling of mRNA, lncRNA, and proteins. Methods: We used this technique to understand the dynamics of mRNA and protein-level differences in healthy, COVID-19-infected and recovered individuals using peripheral blood mononuclear cells (PBMCs). Our results demonstrate that compared to mRNA expression, protein abundance is a better indicator of the disease state. Results: We demonstrate that compared to mRNA expression, protein abundance is a better indicator of the disease state. We observed high levels of cell identity and regulatory markers, CD3E, CD4, CD8A, CD5, CD7, GITR, and KLRB1 in healthy individuals, whereas markers related to cell activation, CD38, CD28, CD69, CD62L, CD14, and CD16 elevated in the SARS-CoV-2 infected patients at both WTA and AbSeq levels. Curiously, in recovered individuals, there was a high expression of cytokine and chemokine receptors (CCR5, CCR7, CCR4, CXCR3, and PTGRD2). We also observed variations in the expression of markers within cell populations under different states. Discussion: Furthermore, our study emphasizes the significance of employing an oligo-based method (AbSeq) that can help in diagnosis, prognosis, and protection from disease/s by identifying cell surface markers that are unique to different cell types or states. It also allows simultaneous study of a vast array of markers, surpassing the constraints of techniques like FACS to query the vast repertoire of proteins.

Transcriptional Signatures of a Dynamic Epilepsy Process Reveal Potential Immune Regulation.

Epilepsy is a progression of development and advancement over time. However, the molecular features of epilepsy were poorly studied from a dynamic developmental perspective. We intend to investigate the key mechanisms in the process of epilepsy by exploring the roles of stage-specifically expressed genes. By using time-course transcriptomic data of epileptic samples, we first analyzed the molecular features of epilepsy in different stages and divided it into progression and remission stages based on their transcriptomic features. 34 stage-specifically expressed genes were then identified by the Tau index and verified in other epileptic datasets. These genes were then enriched for immune-related biological functions. Furthermore, we found that the level of immune infiltration and mechanisms at different stages were different, which may result from different types of immune cells playing leading roles in distinct stages. Our findings indicated an essential role of immune regulation as the potential mechanism of epilepsy development.

scRNA-seq reveals aging-related immune cell types and regulators in vaginal wall from elderly women with pelvic organ prolapse.

Introduction: In the pathology of pelvic organ prolapse (POP), little is known about the contributing role of pelvic microenvironment. Also, the age-related differences in pelvic microenvironment of POP patients is always ignored. In the present study, we investigated the age-related differences in pelvic microenvironment between Young POP patients and Old POP patients, and the novel cell types and critical regulators which contributes to the age-related differences. Methods: Single-cell transcriptomic analyses were used to detect the changes in cell composition and gene expression from the pelvic microenvironment of control group (<60 years), Young POP group (<60 years) and Old POP group (>60 years). Then, immunohistochemistry and immunofluorescence were used to verify the novel cell types and critical regulators in the pelvic microenvironment. Furthermore, histopathological alteration and mechanical property alteration in POP with different ages were revealed by vaginal tissue histology and biomechanical testing. Results: The up-regulated biological process in Old women with POP is mainly related to chronic inflammation, while the up-regulated biological process in Young women with POP is mainly related to extracellular matrix metabolism. Meantime, CSF3+ endothelial cells and FOLR2+ macrophages were found to play a central role in inducing pelvic chronic inflammation. Furthermore, the collagen fiber and mechanical property of POP patients decreased with aging. Conclusions: Taken together, this work provides a valuable resource for deciphering the aging-related immune cell types and the critical regulators in pelvic microenvironment. With better understanding of normal and abnormal events in this pelvic microenvironment, we provided rationales of personalized medicine for POP patients with different ages.

Gender differences in smoking-induced changes in the tumor immune microenvironment.

Both gender and smoking are correlated with prevalence and outcomes in many types of cancers. Tobacco smoke is a known carcinogen through its genotoxicity but can also affect cancer progression through its effect on the immune system. In this study, we aim to evaluate the hypothesis that the effects of smoking on the tumor immune microenvironment will be influenced differently by gender using large-scale analysis of publicly available cancer datasets. We used The Cancer Genomic Atlas (TCGA) datasets (n = 2724) to analyze effects of smoking on different cancer immune subtypes and the relative abundance of immune cell types between male and female cancer patients. We further validated our results by analyzing additional datasets, including Expression Project for Oncology (expO) bulk RNA-seq dataset (n = 1118) and single-cell RNA-seq dataset (n = 14). Results of our study indicate that in female patients, two immune subtypes, C1 and C2, are respectively over and under abundant in smokers vs. never smokers. In males, the only significant difference is underabundance of the C6 subtype in smokers. We identified gender-specific differences in the population of immune cell types between smokers and never smokers in all TCGA and expO cancer types. Increased plasma cell population was identified as the most consistent feature distinguishing smokers and never smokers, especially in current female smokers based on both TCGA and expO data. Our analysis of existing single-cell RNA-seq data further revealed that smoking differentially affects the gene expression profile of cancer patients based on the immune cell type and gender. In our analysis, female and male smokers show different smoking-induced patterns of immune cells in tumor microenvironment. Besides, our results suggest cancer tissues directly exposed to tobacco smoke undergo the most significant changes, but all other tissue types are affected as well. Findings of current study also indicate that changes in the populations of plasma cells and their correlations to survival outcomes are stronger in female current smokers, with implications for cancer immunotherapy of women smokers. In conclusion, results of this study can be used to develop personalized treatment plans for cancer patients who smoke, particularly women smokers, taking into account the unique immune cell profile of their tumors.

Prediction of immune infiltration and prognosis for patients with gastric cancer based on the immune-related genes signature.

Objective: The immune microenvironment influenced clinical outcomes and treatment response of gastric cancer (GC) patients. Though thousands of immune-related genes (IRGs) have been identified, their effects on GC are not fully understood. The objective of the study is to analyze the correlations between the expression and effect of IRGs and clinical outcomes. Moreover, we evaluate the efficacy and value of utilizing the immune-related genes signature as a prognosis prediction model for GC patients. Methods: We identified the differentially expressed IRGs and systematically analyzed their functions. We constructed a novel GC prognostic signature and a new nomogram, Moreover, we explored the infiltrated immune cell types in the immune microenvironment and discussed the genetic variation in GC IRGs. Results: Eight IRGs, including CCL15, MSR1, GNAI1, NR3C1, ITGAV, NMB, AEN, and TGFBR1 were identified. Based on the prognostic signature, GC patients were distinguished into two subtype groups. As verified in multiple datasets, the prognostic signature exhibited good performance in predicting the prognosis (AUC = 0.803, P-value <0.001) and revealed the different clinical features and infiltrated immune cell types in the immune microenvironment. Conclusions: In summary, we found that IRGs contributed to GC prognosis prediction and constructed an IRGs-based GC prognostic signature, which could serve as an effective prognostic stratification tool.

Characterization of Immunoactive and Immunotolerant CD4+ T Cells in Breast Cancer by Measuring Activity of Signaling Pathways That Determine Immune Cell Function.

Cancer immunotolerance may be reversed by checkpoint inhibitor immunotherapy; however, only a subset of patients responds to immunotherapy. The prediction of clinical response in the individual patient remains a challenge. CD4+ T cells play a role in activating adaptive immune responses against cancer, while the conversion to immunosuppression is mainly caused by CD4+ regulatory T cell (Treg) cells. Signal transduction pathways (STPs) control the main functions of immune cells. A novel previously described assay technology enables the quantitative measurement of activity of multiple STPs in individual cell and tissue samples. The activities of the TGFß, NFκB, PI3K-FOXO, JAK-STAT1/2, JAK-STAT3, and Notch STPs were measured in CD4+ T cell subsets and used to investigate cellular mechanisms underlying breast cancer-induced immunotolerance. METHODS: STP activity scores were measured on Affymetrix expression microarray data of the following: (1) resting and immune-activated CD4+ T cells; (2) CD4+ T-helper 1 (Th1) and T-helper 2 (Th2) cells; (3) CD4+ Treg cells; (4) immune-activated CD4+ T cells incubated with breast cancer tissue supernatants; and (5) CD4+ T cells from blood, lymph nodes, and cancer tissue of 10 primary breast cancer patients. RESULTS: CD4+ T cell activation induced PI3K, NFκB, JAK-STAT1/2, and JAK-STAT3 STP activities. Th1, Th2, and Treg cells each showed a typical pathway activity profile. The incubation of activated CD4+ T cells with cancer supernatants reduced the PI3K, NFκB, and JAK-STAT3 pathway activities and increased the TGFß pathway activity, characteristic of an immunotolerant state. Immunosuppressive Treg cells were characterized by high NFκB, JAK-STAT3, TGFß, and Notch pathway activity scores. An immunotolerant pathway activity profile was identified in CD4+ T cells from tumor infiltrate and blood of a subset of primary breast cancer patients, which was most similar to the pathway activity profile in immunosuppressive Treg cells. CONCLUSION: Signaling pathway assays can be used to quantitatively measure the functional immune response state of lymphocyte subsets in vitro and in vivo. Clinical results suggest that, in primary breast cancer, the adaptive immune response of CD4+ T cells may be frequently replaced by immunosuppressive Treg cells, potentially causing resistance to checkpoint inhibition. In vitro study results suggest that this is mediated by soluble factors from cancer tissue. Signaling pathway activity analysis on TIL and/or blood samples may improve response prediction and monitoring response to checkpoint inhibitors and may provide new therapeutic targets (e.g., the Notch pathway) to reduce resistance to immunotherapy.

Analysis of Bulk RNA Sequencing Data Reveals Novel Transcription Factors Associated With Immune Infiltration Among Multiple Cancers.

Tumor-infiltrating immune cells shape the tumor microenvironment and are closely related to clinical outcomes. Several transcription factors (TFs) have also been reported to regulate the antitumor activity and immune cell infiltration. This study aimed to quantify the populations of different immune cells infiltrated in tumor samples based on the bulk RNA sequencing data obtained from 50 cancer patients using the CIBERSORT and the EPIC algorithm. Weighted gene coexpression network analysis (WGCNA) identified eigengene modules strongly associated with tumorigenesis and the activation of CD4+ memory T cells, dendritic cells, and macrophages. TF genes FOXM1, MYBL2, TAL1, and ERG are central in the subnetworks of the eigengene modules associated with immune-related genes. The analysis of The Cancer Genome Atlas (TCGA) cancer data confirmed these findings and further showed that the expression of these potential TF genes regulating immune infiltration, and the immune-related genes that they regulated, was associated with the survival of patients within multiple cancers. Exome-seq was performed on 24 paired samples that also had RNA-seq data. The expression quantitative trait loci (eQTL) analysis showed that mutations were significantly more frequent in the regions flanking the TF genes compared with those of non-TF genes, suggesting a driver role of these TF genes regulating immune infiltration. Taken together, this study presented a practical method for identifying genes that regulate immune infiltration. These genes could be potential biomarkers for cancer prognosis and possible therapeutic targets.

Dissection of Influenza Infection In Vivo by Single-Cell RNA Sequencing.

The influenza virus is a major cause of morbidity and mortality worldwide. Yet, both the impact of intracellular viral replication and the variation in host response across different cell types remain uncharacterized. Here we used single-cell RNA sequencing to investigate the heterogeneity in the response of lung tissue cells to in vivo influenza infection. Analysis of viral and host transcriptomes in the same single cell enabled us to resolve the cellular heterogeneity of bystander (exposed but uninfected) as compared with infected cells. We reveal that all major immune and non-immune cell types manifest substantial fractions of infected cells, albeit at low viral transcriptome loads relative to epithelial cells. We show that all cell types respond primarily with a robust generic transcriptional response, and we demonstrate novel markers specific for influenza-infected as opposed to bystander cells. These findings open new avenues for targeted therapy aimed exclusively at infected cells.

Systems Immunology: Learning the Rules of the Immune System.

Given the many cell types and molecular components of the human immune system, along with vast variations across individuals, how should we go about developing causal and predictive explanations of immunity? A central strategy in human studies is to leverage natural variation to find relationships among variables, including DNA variants, epigenetic states, immune phenotypes, clinical descriptors, and others. Here, we focus on how natural variation is used to find patterns, infer principles, and develop predictive models for two areas: (a) immune cell activation-how single-cell profiling boosts our ability to discover immune cell types and states-and (b) antigen presentation and recognition-how models can be generated to predict presentation of antigens on MHC molecules and their detection by T cell receptors. These are two examples of a shift in how we find the drivers and targets of immunity, especially in the human system in the context of health and disease.

Toward defining a 'lineage'--The case for dendritic cells.

The immune system consists of a heterogeneous ensemble of cell types that immunologists have tried to classify and order for decades. This classification has relied on varying criteria, resulting in major debates in the immunology community. Discovered in the late 1970s [1], dendritic cells (DCs) are no exception, and their membership to a distinct immune lineage is still vividly debated [2-6]. Here, we review recent work on the origin of DCs and discuss the possible definition of a separate 'DC lineage'.