scholarly journals Gene Expression: the Key to Understanding HIV-1 Infection?

2020 ◽  
Vol 84 (2) ◽  
Author(s):  
Melinda Judge ◽  
Erica Parker ◽  
Denise Naniche ◽  
Peter Le Souëf
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Host Response ◽  
Acute Infection ◽  
Cell Types ◽  
Tissue Type ◽  
Full Potential ◽  
Cell Tissue ◽  
Gene Expression Dysregulation ◽  
Living With Hiv

SUMMARY Gene expression profiling of the host response to HIV infection has promised to fill the gaps in our knowledge and provide new insights toward vaccine and cure. However, despite 20 years of research, the biggest questions remained unanswered. A literature review identified 62 studies examining gene expression dysregulation in samples from individuals living with HIV. Changes in gene expression were dependent on cell/tissue type, stage of infection, viremia, and treatment status. Some cell types, notably CD4+ T cells, exhibit upregulation of cell cycle, interferon-related, and apoptosis genes consistent with depletion. Others, including CD8+ T cells and natural killer cells, exhibit perturbed function in the absence of direct infection with HIV. Dysregulation is greatest during acute infection. Differences in study design and data reporting limit comparability of existing research and do not as yet provide a coherent overview of gene expression in HIV. This review outlines the extraordinarily complex host response to HIV and offers recommendations to realize the full potential of HIV host transcriptomics.

scholarly journals GSDMA drives the most replicated association with asthma in naïve CD4+ T cells

2019 ◽  
Author(s):  
Anne-Marie Madore ◽  
Lucile Pain ◽  
Anne-Marie Boucher-Lafleur ◽  
Jolyane Meloche ◽  
Andréanne Morin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
T Cells ◽  
Genetic Variants ◽  
Immune Cell ◽  
Cell Types ◽  
Sequencing Data ◽  
Opposite Pattern ◽  
Genetic Mechanisms ◽  
New Gene

AbstractBackgroundThe 17q12-21 locus is the most replicated association with asthma. However, no study had described the genetic mechanisms underlying this association considering all genes of the locus in immune cell samples isolated from asthmatic and non-asthmatic individuals.ObjectiveThis study takes benefit of samples from naïve CD4+ T cells and eosinophils isolated from the same 200 individuals to describe specific interactions between genetic variants, gene expression and DNA methylation levels for the 17q12-21 asthma locus.Methods and ResultsAfter isolation of naïve CD4+ T cells and eosinophils from blood samples, next generation sequencing was used to measure DNA methylation levels and gene expression counts. Genetic interactions were then evaluated considering genetic variants from imputed genotype data. In naïve CD4+ T cells but not eosinophils, 20 SNPs in the fourth and fifth haplotype blocks modulated both GSDMA expression and methylation levels, showing an opposite pattern of allele frequencies and expression counts in asthmatics compared to controls. Moreover, negative correlations have been measured between methylation levels of CpG sites located within the 1.5 kb region from the transcription start site of GSDMA and its expression counts.ConclusionAvailability of sequencing data from two key cell types isolated from asthmatic and non-asthmatic individuals allowed identifying a new gene in naïve CD4+ T cells that drives the association with the 17q12-21 locus, leading to a better understanding of the genetic mechanisms taking place in it.

Exploiting Endogenous Micro-RNAs to Avoid off-Target Transgene Expression

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3296-3296
Author(s):  
Raul Teruel Montoya ◽  
Xianguo Kong ◽  
Shaji Abraham ◽  
Lin Ma ◽  
Leonard C. Edelstein ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Cell Lines ◽  
Binding Sites ◽  
Transgene Expression ◽  
Cell Types ◽  
Jurkat Cells ◽  
Cell Type ◽  
Hematological Disorders

Abstract Abstract 3296 Genetic modification of hematopoietic stem cells (HSCs) has the potential to benefit acquired and congenital hematological disorders. Despite the use of so-called “tissue-specific” promoters to drive expression of the desired transgene, off-target (and consequent deleterious) effects have been observed. MicroRNAs (miRNAs) are important regulators of gene expression. They associate with Argonaute proteins and most typically target 3'UTRs, where complementary base-pairing results in repressed gene expression via RNA decay and translation inhibition. Most miRNAs are ubiquitously expressed, and although some are claimed to be “tissue specific,” such claims have generally not been rigorously validated. The long-term goal of this work is identifying “cell preferential” miRNA expression that could be exploited in expression vectors to minimize off-target transgene expression in HSCs. Initially, total RNA was extracted with Trizol from the megakaryocyte and T-lymphocyte cell lines, Meg-01 and Jurkat, and miRNAs were profiled by Nanostring technology (Nanostring Technologies, Denver, CO). MiR-495 was determined to be highly expressed in Meg-01 and very low in Jurkat cells. A luciferase reporter construct was generated with four canonical binding sites for miR-495 in the 3'UTR and transfected into both cell lines. Compared to control vector without miR-495 binding sites, luciferase expression showed a 50% reduction in Meg-01 cells, but no knock down in Jurkat cells. These experiments indicated that different levels of endogenous miRNA levels can regulate transgene expression through a novel design in the 3'UTR. We next turned our attention to human hematopoietic cells. We reasoned that the long-term goal of minimal off-target transgene expression in HSCs would require knowledge of miRNAs that had little or no detectable expression (“selectively reduced [SR]”) in one cell type and were highly expressed in other cell types. In this manner, the transgene expression would be dampened only in the non-target cells. As a surrogate for bone marrow progenitors and as proof of principle, we used primary cells in normal human peripheral blood. T-cells, B-cells, platelets and granulocytes were purified by density centrifugation followed by immunoselection from five healthy human donors. Flow cytometry using membrane specific markers demonstrate >97% purity of each specific cell preparation. Total RNA was extracted and miRNAs were profiled as above. First, we identified 277 miRNAs that were differentially expressed between any pair of cell types (p-value<0.05 by ANOVA). Second, we performed ranked pair-wise comparisons across all cell types to determine SR miRNAs. This analysis revealed 5 platelet SR-miRNAs, 6 B-cell SR-miRNAs, 2 T-cell SR-miRNAs and 4 granulocyte SR-miRNAs. Lastly, we considered which of these 17 SR-miRNAs would be the best single SR-miRNA within and across cell types. SR-miRNAs were normalized to let-7b, a miRNA we determined to be equivalently expressed across all cell types, and hence, an ideal normalizer. Lineage-specific SR-miRNAs were selected based on extremely low expression in only one cell type and highest fold change of expression compared to the other cell types. The best SR-miRNAs were miR-29b (SR in platelets), miR-125a-5p (SR in B-cells) and miR-146a (SR in granulocytes). The SR expression levels of these 3 miRNAs were validated by qRT-PCR. Our analysis identified no good SR-miRNAs in T-cells. On-going experiments are testing the selective effects of the SR miRNAs in lentiviral vector infection of cord blood CD34+ cells differentiated along specific lineages. In summary, we have demonstrated in hematopoietic cell lines that SR endogenous miRNAs can regulate the expression of transgenes via tandem arrangement of their target sites in the 3'UTR. Additionally, we have identified miRNAs that are specifically expressed at a very low level in one blood cell type and at high levels in other cell types. These miRNAs could potentially be utilized as new biological tools in gene therapy for hematological disorders to restrict transgene expression and avoid the negative consequences of off-target expression. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Landscape of T Cells Transcriptional and Metabolic Modules During HIV Infection Based on Weighted Gene Co-expression Network Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Jianting Xu ◽  
Jiahui Pan ◽  
Xin Liu ◽  
Nan Zhang ◽  
Xinyue Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
Network Analysis ◽  
Hiv Infection ◽  
Metabolic Pathways ◽  
Cell Types ◽  
Core Gene ◽  
Ppar Signaling ◽  
Immunodeficiency Syndrome

Human immunodeficiency virus (HIV) causes acquired immunodeficiency syndrome (AIDS). HIV infection affects the functions and metabolism of T cells, which may determine the fate of patients; however, the specific pathways activated in different T-cell subtypes (CD4+ and CD8+ T cells) at different stages of infection remain unclear. We obtained transcriptome data of five individuals each with early HIV infection, chronic progressive HIV infection, and no HIV infection. Weighted gene co-expression network analysis was used to evaluate changes in gene expression to determine the antiviral response. An advanced metabolic algorithm was then applied to compare the alterations in metabolic pathways in the two T-cell subtypes at different infection stages. We identified 23 and 20 co-expressed gene modules in CD4+ T and CD8+ T cells, respectively. CD4+ T cells from individuals in the early HIV infection stage were enriched in genes involved in metabolic and infection-related pathways, whereas CD8+ T cells were enriched in genes involved in cell cycle and DNA replication. Three key modules were identified in the network common to the two cell types: NLRP1 modules, RIPK1 modules, and RIPK2 modules. The specific role of NLRP1 in the regulation of HIV infection in the human body remains to be determined. Metabolic functional analysis of the two cells showed that the significantly altered metabolic pathways after HIV infection were valine, leucine, and isoleucine degradation; beta-alanine metabolism; and PPAR signaling pathways. In summary, we found the core gene expression modules and different pathways activated in CD4+ and CD8+ T cells, along with changes in their metabolic pathways during HIV infection progression. These findings can provide an overall resource for establishing biomarkers to facilitate early diagnosis and potential guidance for new targeted therapeutic strategies.

scholarly journals Single-cell RNA sequencing reveals heterogeneous tumor and immune cell populations in early-stage lung adenocarcinomas harboring EGFR mutations

Oncogene ◽  
2020 ◽  
Author(s):  
Di He ◽  
Di Wang ◽  
Ping Lu ◽  
Nan Yang ◽  
Zhigang Xue ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Single Cell ◽  
Tumor Cells ◽  
Rna Sequencing ◽  
Early Stage ◽  
Cell Types ◽  
Egfr Mutations ◽  
Advanced Tumor ◽  
Single Cell Rna Sequencing

Abstract Lung adenocarcinoma (LUAD) harboring EGFR mutations prevails in Asian population. However, the inter-patient and intra-tumor heterogeneity has not been addressed at single-cell resolution. Here we performed single-cell RNA sequencing (scRNA-seq) of total 125,674 cells from seven stage-I/II LUAD samples harboring EGFR mutations and five tumor-adjacent lung tissues. We identified diverse cell types within the tumor microenvironment (TME) in which myeloid cells and T cells were the most abundant stromal cell types in tumors and adjacent lung tissues. Within tumors, accompanied by an increase in CD1C+ dendritic cells, the tumor-associated macrophages (TAMs) showed pro-tumoral functions without signature gene expression of defined M1 or M2 polarization. Tumor-infiltrating T cells mainly displayed exhausted and regulatory T-cell features. The adenocarcinoma cells can be categorized into different subtypes based on their gene expression signatures in distinct pathways such as hypoxia, glycolysis, cell metabolism, translation initiation, cell cycle, and antigen presentation. By performing pseudotime trajectory, we found that ELF3 was among the most upregulated genes in more advanced tumor cells. In response to secretion of inflammatory cytokines (e.g., IL1B) from immune infiltrates, ELF3 in tumor cells was upregulated to trigger the activation of PI3K/Akt/NF-κB pathway and elevated expression of proliferation and anti-apoptosis genes such as BCL2L1 and CCND1. Taken together, our study revealed substantial heterogeneity within early-stage LUAD harboring EGFR mutations, implicating complex interactions among tumor cells, stromal cells and immune infiltrates in the TME.

scholarly journals Comprehensive analysis of immune cell enrichment in the tumor microenvironment of head and neck squamous cell carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ikko Mito ◽  
Hideyuki Takahashi ◽  
Reika Kawabata-Iwakawa ◽  
Shota Ida ◽  
Hiroe Tada ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Tumor Microenvironment ◽  
Head And Neck ◽  
Gene Expression Data ◽  
Immune Cell ◽  
Cell Types ◽  
Expression Data ◽  
Immune Microenvironment ◽  
Cancer Tissues

AbstractHead and neck squamous carcinoma (HNSCC) is highly infiltrated by immune cells, including tumor-infiltrating lymphocytes and myeloid lineage cells. In the tumor microenvironment, tumor cells orchestrate a highly immunosuppressive microenvironment by secreting immunosuppressive mediators, expressing immune checkpoint ligands, and downregulating human leukocyte antigen expression. In the present study, we aimed to comprehensively profile the immune microenvironment of HNSCC using gene expression data obtained from public database. We calculated enrichment scores of 33 immune cell types based on gene expression data of HNSCC tissues and adjacent non-cancer tissues. Based on these scores, we performed non-supervised clustering and identified three immune signatures—cold, lymphocyte, and myeloid/dendritic cell (DC)—based on the clustering results. We then compared the clinical and biological features of the three signatures. Among HNSCC and non-cancer tissues, human papillomavirus (HPV)-positive HNSCCs exhibited the highest scores in various immune cell types, including CD4+ T cells, CD8+ T cells, B cells, plasma cells, basophils, and their subpopulations. Among the three immune signatures, the proportions of HPV-positive tumors, oropharyngeal cancers, early T tumors, and N factor positive cases were significantly higher in the lymphocyte signature than in other signatures. Among the three signatures, the lymphocyte signature showed the longest overall survival (OS), especially in HPV-positive patients, whereas the myeloid/DC signature demonstrated the shortest OS in these patients. Gene set enrichment analysis revealed the upregulation of several pathways related to inflammatory and proinflammatory responses in the lymphocyte signature. The expression of PRF1, IFNG, GZMB, CXCL9, CXCL10, PDCD1, LAG3, CTLA4, HAVCR2, and TIGIT was the highest in the lymphocyte signature. Meanwhile, the expression of PD-1 ligand genes CD274 and PDCD1LG2 was highest in the myeloid/DC signature. Herein, our findings revealed the transcriptomic landscape of the immune microenvironment that closely reflects the clinical and biological significance of HNSCC, indicating that molecular profiling of the immune microenvironment can be employed to develop novel biomarkers and precision immunotherapies for HNSCC.

scholarly journals Integrative transcriptomic analysis of SLE reveals IFN-driven cross-talk between immune cells

2020 ◽  
Author(s):  
Bharat Panwar ◽  
Benjamin J. Schmiedel ◽  
Shu Liang ◽  
Brandie White ◽  
Enrique Rodriguez ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Autoimmune Disease ◽  
Cross Talk ◽  
Immune Cell ◽  
Cell Types ◽  
Cell Populations ◽  
Multiple Cell ◽  
Classical Monocytes ◽  
Multiple Immune Cell

ABSTRACTThe systemic lupus erythematosus (SLE) is an incurable autoimmune disease disproportionately affecting women and may lead to damage in multiple different organs. The marked heterogeneity in its clinical manifestations is a major obstacle in finding targeted treatments and involvement of multiple immune cell types further increases this complexity. Thus, identifying molecular subtypes that best correlate with disease heterogeneity and severity as well as deducing molecular cross-talk among major immune cell types that lead to disease progression are critical steps in the development of more informed therapies for SLE. Here we profile and analyze gene expression of six major circulating immune cell types from patients with well-characterized SLE (classical monocytes (n=64), T cells (n=24), neutrophils (n=24), B cells (n=20), conventional (n=20) and plasmacytoid (n=22) dendritic cells) and from healthy control subjects. Our results show that the interferon (IFN) response signature was the major molecular feature that classified SLE patients into two distinct groups: IFN-signature negative (IFNneg) and positive (IFNpos). We show that the gene expression signature of IFN response was consistent (i) across all immune cell types, (ii) all single cells profiled from three IFNpos donors using single-cell RNA-seq, and (iii) longitudinal samples of the same patient. For a better understanding of molecular differences of IFNpos versus IFNneg patients, we combined differential gene expression analysis with differential Weighted Gene Co-expression Network Analysis (WGCNA), which revealed a relatively small list of genes from classical monocytes including two known immune modulators, one the target of an approved therapeutic for SLE (TNFSF13B/BAFF: belimumab) and one itself a therapeutic for Rheumatoid Arthritis (IL1RN: anakinra). For a more integrative understanding of the cross-talk among different cell types and to identify potentially novel gene or pathway connections, we also developed a novel gene co-expression analysis method for joint analysis of multiple cell types named integrated WGNCA (iWGCNA). This method revealed an interesting cross-talk between T and B cells highlighted by a significant enrichment in the expression of known markers of T follicular helper cells (Tfh), which also correlate with disease severity in the context of IFNpos patients. Interestingly, higher expression of BAFF from all myeloid cells also shows a strong correlation with enrichment in the expression of genes in T cells that may mark circulating Tfh cells or related memory cell populations. These cell types have been shown to promote B cell class-switching and antibody production, which are well-characterized in SLE patients. In summary, we generated a large-scale gene expression dataset from sorted immune cell populations and present a novel computational approach to analyze such data in an integrative fashion in the context of an autoimmune disease. Our results reveal the power of a hypothesis-free and data-driven approach to discover drug targets and reveal novel cross-talk among multiple immune cell types specific to a subset of SLE patients. This approach is immediately useful for studying autoimmune diseases and is applicable in other contexts where gene expression profiling is possible from multiple cell types within the same tissue compartment.

scholarly journals Genetic determinants of chromatin accessibility in T cell activation across humans

2016 ◽  
Author(s):  
Rachel E. Gate ◽  
Christine S. Cheng ◽  
Aviva P. Aiden ◽  
Atsede Siba ◽  
Marcin Tabaka ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
T Cell Activation ◽  
Genetic Variants ◽  
Cell Activation ◽  
Cell Types ◽  
Regulatory Elements ◽  
Specific Cell ◽  
Accessible Chromatin

AbstractOver 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, we analyzed Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) and RNA-seq profiles from activated CD4+ T cells of up to 105 healthy donors. We found that regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution, in patterns consistent with the 3D organization of chromosomes measured by in situ Hi-C in T cells. 15% of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak through disrupting binding sites for transcription factors important for T cell differentiation and activation. These ATAC quantitative trait nucleotides (ATAC-QTNs) have the largest effects on co-accessible peaks, are associated with gene expression from the same aliquot of cells, are rarely affecting core binding motifs, and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis- regulatory elements, in isolation or in concert, to influence gene expression in primary immune cells that play a key role in many human diseases.

scholarly journals Nfat

2002 ◽  
Vol 156 (5) ◽  
pp. 771-774 ◽  
Author(s):  
Valerie Horsley ◽  
Grace K. Pavlath
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Transcription Factors ◽  
Immune System ◽  
Cell Types ◽  
Cytokine Gene Expression ◽  
Nuclear Factor ◽  
Cytokine Gene ◽  
Activated T Cells ◽  
Control Of Gene Expression

The nuclear factor of activated T cells (NFAT) proteins are a family of transcription factors whose activation is controlled by calcineurin, a Ca2+-dependent phosphatase. Originally identified in T cells as inducers of cytokine gene expression, NFAT proteins play varied roles in cells outside of the immune system. This review addresses the recent data implicating NFAT in the control of gene expression influencing the development and adaptation of numerous mammalian cell types.

scholarly journals Exploring inflammatory signatures in arthritic joint biopsies with Spatial Transcriptomics

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Konstantin Carlberg ◽  
Marina Korotkova ◽  
Ludvig Larsson ◽  
Anca I. Catrina ◽  
Patrik L. Ståhl ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Immune Cell ◽  
Memory T Cells ◽  
Inflammatory Diseases ◽  
Adaptive Immune Response ◽  
Cell Types ◽  
Effector Memory ◽  
Cellular Mechanisms ◽  
Chronic Inflammatory Diseases

AbstractLately it has become possible to analyze transcriptomic profiles in tissue sections with retained cellular context. We aimed to explore synovial biopsies from rheumatoid arthritis (RA) and spondyloarthritis (SpA) patients, using Spatial Transcriptomics (ST) as a proof of principle approach for unbiased mRNA studies at the site of inflammation in these chronic inflammatory diseases. Synovial tissue biopsies from affected joints were studied with ST. The transcriptome data was subjected to differential gene expression analysis (DEA), pathway analysis, immune cell type identification using Xcell analysis and validation with immunohistochemistry (IHC). The ST technology allows selective analyses on areas of interest, thus we analyzed morphologically distinct areas of mononuclear cell infiltrates. The top differentially expressed genes revealed an adaptive immune response profile and T-B cell interactions in RA, while in SpA, the profiles implicate functions associated with tissue repair. With spatially resolved gene expression data, overlaid on high-resolution histological images, we digitally portrayed pre-selected cell types in silico. The RA displayed an overrepresentation of central memory T cells, while in SpA effector memory T cells were most prominent. Consequently, ST allows for deeper understanding of cellular mechanisms and diversity in tissues from chronic inflammatory diseases.

scholarly journals Cell and tissue type independent age-associated DNA methylation changes are not rare but common

2018 ◽  
Author(s):  
Tianyu Zhu ◽  
Shijie C Zheng ◽  
Dirk S. Paul ◽  
S. Horvath ◽  
Andrew E. Teschendorff
Keyword(s):  
Dna Methylation ◽  
Cell Types ◽  
Tissue Type ◽  
Tissue Cell ◽  
Cell Type ◽  
Tissue Specific ◽  
Cell Tissue ◽  
A Cell ◽  
High Degree ◽  
Do So

AbstractAge-associated DNA methylation changes have been widely reported across many different tissue and cell types. Epigenetic ‘clocks’ that can predict chronological age with a surprisingly high degree of accuracy appear to do so independently of tissue and cell-type, suggesting that a component of epigenetic drift is cell-type independent. However, the relative amount of age-associated DNAm changes that are specific to a cell or tissue type versus the amount that occurs independently of cell or tissue type is unclear and a matter of debate, with a recent study concluding that most epigenetic drift is tissue-specific. Here, we perform a novel comprehensive statistical analysis, including matched multi cell-type and multi-tissue DNA methylation profiles from the same individuals and adjusting for cell-type heterogeneity, demonstrating that a substantial amount of epigenetic drift, possibly over 70%, is shared between significant numbers of different tissue/cell types. We further show that ELOVL2 is not unique and that many other CpG sites, some mapping to genes in the Wnt and glutamate receptor signaling pathways, are altered with age across at least 10 different cell/tissue types. We propose that while most age-associated DNAm changes are shared between cell-types that the putative functional effect is likely to be tissue-specific.

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