scholarly journals In vivo reprogramming of murine host immune response genes following Leishmania major infection.

2021 ◽  
Author(s):  
Gopinath Venugopal ◽  
Jordan T. Bird ◽  
Charity L. Washam ◽  
Hayden Roys ◽  
Anne Bowlin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Antigen Presentation ◽  
Rna Sequencing ◽  
Cell Types ◽  
Host Immune Response ◽  
Rna Seq ◽  
Major Infection ◽  
Presentation Pathway

Leishmania parasites cause cutaneous leishmaniasis (CL), a pathologic disease characterized by disfiguring, ulcerative skin lesions. Both parasite and host gene expression following infection with various Leishmania species has been investigated in vitro, but global transcriptional analysis following L. major infection in vivo is lacking. Thus, we conducted a comprehensive transcriptomic profiling study combining bulk RNA sequencing (RNA-Seq) and single-cell RNA sequencing (scRNA-Seq) to identify global changes in gene expression in vivo following L. major infection. Bulk RNA-Seq analysis revealed that host immune response pathways like the antigen processing and presentation pathway were significantly enriched amongst differentially expressed genes (DEGs) upon infection, while ribosomal pathways were significantly downregulated in infected mice compared to naive controls. scRNA-Seq analyses revealed cellular heterogeneity including distinct resident and recruited cell types in the skin following murine L. major infection. Within the individual immune cell types, several DEGs indicative of many interferon induced GTPases and antigen presentation molecules were significantly enhanced in the infected ears including macrophages (Gbp2, H2-K1, H2-Aa, H2-Ab1), resident macrophages (H2-K1, H2-D1, Gbp4, Gbp8, Gbp2), and inflammatory monocytes (Gbp2, Gbp5, Gbp7, Gbp3). Ingenuity Pathway Analysis of scRNA-Seq data indicated the antigen presentation pathway was increased with infection, while EIF2 signaling is the top downregulated pathway followed by eIF4/p70S6k and mTOR signaling in multiple cell types including macrophages, BECs, and LECs. Altogether, this transcriptomic profile highlights known recruitment of myeloid cells to lesions and recognizes a previously undefined role for EIF2 signaling in murine L. major infection in vivo.

scholarly journals Gene expression in tonsils in swine following infection with porcine reproductive and respiratory syndrome virus

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Qian Dong ◽  
Joan K. Lunney ◽  
Kyu-Sang Lim ◽  
Yet Nguyen ◽  
Andrew S. Hess ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Immune Responses ◽  
Cell Types ◽  
Host Immune Response ◽  
Respiratory Syndrome Virus ◽  
Rna Seq ◽  
Cell Composition ◽  
Multiple Cell ◽  
Mechanisms Of Persistence

Abstract Background Porcine reproductive and respiratory syndrome (PRRS) is a threat to pig production worldwide. Our objective was to understand mechanisms of persistence of PRRS virus (PRRSV) in tonsil. Transcriptome data from tonsil samples collected at 42 days post infection (dpi) were generated by RNA-seq and NanoString on 51 pigs that were selected to contrast the two PRRSV isolates used, NVSL and KS06, high and low tonsil viral level at 42 dpi, and the favorable and unfavorable genotypes at a genetic marker (WUR) for the putative PRRSV resistance gene GBP5. Results The number of differentially expressed genes (DEGs) differed markedly between models with and without accounting for cell-type enrichments (CE) in the samples that were predicted from the RNA-seq data. This indicates that differences in cell composition in tissues that consist of multiple cell types, such as tonsil, can have a large impact on observed differences in gene expression. Based on both the NanoString and the RNA-seq data, KS06-infected pigs showed greater activation, or less inhibition, of immune response in tonsils at 42 dpi than NVSL-infected pigs, with and without accounting for CE. This suggests that the NVSL virus may be better than the KS06 virus at evading host immune response and persists in tonsils by weakening, or preventing, host immune responses. Pigs with high viral levels showed larger CE of immune cells than low viral level pigs, potentially to trigger stronger immune responses. Presence of high tonsil virus was associated with a stronger immune response, especially innate immune response through interferon signaling, but these differences were not significant when accounting for CE. Genotype at WUR was associated with different effects on immune response in tonsils of pigs during the persistence stage, depending on viral isolate and tonsil viral level. Conclusions Results of this study provide insights into the effects of PRRSV isolate, tonsil viral level, and WUR genotype on host immune response and into potential mechanisms of PRRSV persistence in tonsils that could be targeted to improve strategies to reduce viral rebreaks. Finally, to understand transcriptome responses in tissues that consist of multiple cell types, it is important to consider differences in cell composition.

scholarly journals Building an RNA Sequencing Transcriptome of the Central Nervous System

2016 ◽  
Vol 22 (6) ◽  
pp. 579-592 ◽  
Author(s):  
Xiaomin Dong ◽  
Yanan You ◽  
Jia Qian Wu
Keyword(s):  
Gene Expression ◽  
Central Nervous System ◽  
Nervous System ◽  
Rna Sequencing ◽  
Large Scale ◽  
Expression Profiles ◽  
Cell Types ◽  
Specific Cell ◽  
Rna Seq ◽  
The Central Nervous System

The composition and function of the central nervous system (CNS) is extremely complex. In addition to hundreds of subtypes of neurons, other cell types, including glia (astrocytes, oligodendrocytes, and microglia) and vascular cells (endothelial cells and pericytes) also play important roles in CNS function. Such heterogeneity makes the study of gene transcription in CNS challenging. Transcriptomic studies, namely the analyses of the expression levels and structures of all genes, are essential for interpreting the functional elements and understanding the molecular constituents of the CNS. Microarray has been a predominant method for large-scale gene expression profiling in the past. However, RNA-sequencing (RNA-Seq) technology developed in recent years has many advantages over microarrays, and has enabled building more quantitative, accurate, and comprehensive transcriptomes of the CNS and other systems. The discovery of novel genes, diverse alternative splicing events, and noncoding RNAs has remarkably expanded the complexity of gene expression profiles and will help us to understand intricate neural circuits. Here, we discuss the procedures and advantages of RNA-Seq technology in mammalian CNS transcriptome construction, and review the approaches of sample collection as well as recent progress in building RNA-Seq-based transcriptomes from tissue samples and specific cell types.

scholarly journals Cross-species Transcriptomic Comparison of In Vitro and In Vivo Mammalian Neural Cells

2015 ◽  
Vol 9 ◽  
pp. BBI.S33124 ◽  
Author(s):  
Peter R. LoVerso ◽  
Christopher M. Wachter ◽  
Feng Cui
Keyword(s):  
Gene Expression ◽  
Transcript Abundance ◽  
Cell Types ◽  
Mammalian Brain ◽  
Neural Cells ◽  
Rna Seq ◽  
Commercial Sources ◽  
And Function

The mammalian brain is characterized by distinct classes of cells that differ in morphology, structure, signaling, and function. Dysregulation of gene expression in these cell populations leads to various neurological disorders. Neural cells often need to be acutely purified from animal brains for research, which requires complicated procedure and specific expertise. Primary culture of these cells in vitro is a viable alternative, but the differences in gene expression of cells grown in vitro and in vivo remain unclear. Here, we cultured three major neural cell classes of rat brain (ie, neurons, astrocytes, and oligodendrocyte precursor cells [OPCs]) obtained from commercial sources. We measured transcript abundance of these cell types by RNA sequencing (RNA-seq) and compared with their counterparts acutely purified from mouse brains. Cross-species RNA-seq data analysis revealed hundreds of genes that are differentially expressed between the cultured and acutely purified cells. Astrocytes have more such genes compared to neurons and OPCs, indicating that signaling pathways are greatly perturbed in cultured astrocytes. This dataset provides a powerful resource to demonstrate the similarities and differences of biological processes in mammalian neural cells grown in vitro and in vivo at the molecular level.

scholarly journals An elastic-net logistic regression approach to generate classifiers and gene signatures for types of immune cells and T helper cell subsets

2019 ◽  
Author(s):  
Arezo Torang ◽  
Paraag Gupta ◽  
David J. Klinke
Keyword(s):  
Machine Learning ◽  
Immune Response ◽  
Immune Cell ◽  
Cell Types ◽  
Host Immune Response ◽  
T Helper Cell ◽  
Helper Cell ◽  
Rna Seq ◽  
T Helper ◽  
Gene Signatures

AbstractBackgroundHost immune response is coordinated by a variety of different specialized cell types that vary in time and location. While host immune response can be studied using conventional low-dimensional approaches, advances in transcriptomics analysis may provide a less biased view. Yet, leveraging transcriptomics data to identify immune cell subtypes presents challenges for extracting informative gene signatures hidden within a high dimensional transcriptomics space characterized by low sample numbers with noisy and missing values. To address these challenges, we explore using machine learning methods to select gene subsets and estimate gene coefficients simultaneously.ResultsElastic-net logistic regression, a type of machine learning, was used to construct separate classifiers for ten different types of immune cell and for five T helper cell subsets. The resulting classifiers were then used to develop gene signatures that best discriminate among immune cell types and T helper cell subsets using RNA-seq datasets. We validated the approach using single-cell RNA-seq (scRNA-seq) datasets, which gave consistent results. In addition, we classified cell types that were previously unannotated. Finally, we benchmarked the proposed gene signatures against other existing gene signatures.ConclusionsDeveloped classifiers can be used as priors in predicting the extent and functional orientation of the host immune response in diseases, such as cancer, where transcriptomic profiling of bulk tissue samples and single cells are routinely employed. Information that can provide insight into the mechanistic basis of disease and therapeutic response. The source code and documentation are available through GitHub: https://github.com/KlinkeLab/ImmClass2019.

scholarly journals Cell Dissociation from Butterfly Pupal Wing Tissues for Single-Cell RNA Sequencing

2020 ◽  
Vol 3 (4) ◽  
pp. 72
Author(s):  
Anupama Prakash ◽  
Antónia Monteiro
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cells ◽  
Expression Patterns ◽  
Cell Types ◽  
Rna Seq ◽  
Bicyclus Anynana ◽  
Single Cell Sequencing ◽  
Pupal Wing

Butterflies are well known for their beautiful wings and have been great systems to understand the ecology, evolution, genetics, and development of patterning and coloration. These color patterns are mosaics on the wing created by the tiling of individual units called scales, which develop from single cells. Traditionally, bulk RNA sequencing (RNA-seq) has been used extensively to identify the loci involved in wing color development and pattern formation. RNA-seq provides an averaged gene expression landscape of the entire wing tissue or of small dissected wing regions under consideration. However, to understand the gene expression patterns of the units of color, which are the scales, and to identify different scale cell types within a wing that produce different colors and scale structures, it is necessary to study single cells. This has recently been facilitated by the advent of single-cell sequencing. Here, we provide a detailed protocol for the dissociation of cells from Bicyclus anynana pupal wings to obtain a viable single-cell suspension for downstream single-cell sequencing. We outline our experimental design and the use of fluorescence-activated cell sorting (FACS) to obtain putative scale-building and socket cells based on size. Finally, we discuss some of the current challenges of this technique in studying single-cell scale development and suggest future avenues to address these challenges.

scholarly journals Assessment of a highly multiplexed RNA sequencing platform and comparison to existing high-throughput gene expression profiling techniques

2018 ◽  
Author(s):  
Eric Reed ◽  
Elizabeth Moses ◽  
Xiaohui Xiao ◽  
Gang Liu ◽  
Joshua Campbell ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Differential Gene Expression ◽  
Low Cost ◽  
Digital Gene Expression ◽  
Data Generation ◽  
Rna Seq ◽  
Sequencing Platform ◽  
Differential Gene

AbstractThe need to reduce per sample cost of RNA-seq profiling for scalable data generation has led to the emergence of highly multiplexed RNA-seq. These technologies utilize barcoding of cDNA sequences in order to combine samples into single sequencing lane to be separated during data processing. In this study, we report the performance of one such technique denoted as sparse full length sequencing (SFL), a ribosomal RNA depletion-based RNA sequencing approach that allows for the simultaneous sequencing of 96 samples and higher. We offer comparisons to well established single-sample techniques, including: full coverage Poly-A capture RNA-seq and microarray, as well as another low-cost highly multiplexed technique known as 3’ digital gene expression (3’DGE). Data was generated for a set of exposure experiments on immortalized human lung epithelial (AALE) cells in a two-by-two study design, in which samples received both genetic and chemical perturbations of known oncogenes/tumor suppressors and lung carcinogens. SFL demonstrated improved performance over 3’DGE in terms of coverage, power to detect differential gene expression, and biological recapitulation of patterns of differential gene expression from in vivo lung cancer mutation signatures.

scholarly journals Mitochondrial Mistranslation in Brain Provokes a Metabolic Response Which Mitigates the Age-Associated Decline in Mitochondrial Gene Expression

2021 ◽  
Vol 22 (5) ◽  
pp. 2746
Author(s):  
Dimitri Shcherbakov ◽  
Reda Juskeviciene ◽  
Adrián Cortés Sanchón ◽  
Margarita Brilkova ◽  
Hubert Rehrauer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Metabolic Response ◽  
Mitochondrial Gene ◽  
Tca Cycle ◽  
Brain Mitochondria ◽  
Mitochondrial Gene Expression ◽  
Rna Seq ◽  
The Tca Cycle ◽  
Neurological Phenotype

Mitochondrial misreading, conferred by mutation V338Y in mitoribosomal protein Mrps5, in-vivo is associated with a subtle neurological phenotype. Brain mitochondria of homozygous knock-in mutant Mrps5V338Y/V338Y mice show decreased oxygen consumption and reduced ATP levels. Using a combination of unbiased RNA-Seq with untargeted metabolomics, we here demonstrate a concerted response, which alleviates the impaired functionality of OXPHOS complexes in Mrps5 mutant mice. This concerted response mitigates the age-associated decline in mitochondrial gene expression and compensates for impaired respiration by transcriptional upregulation of OXPHOS components together with anaplerotic replenishment of the TCA cycle (pyruvate, 2-ketoglutarate).

scholarly journals H-Ras gene takes part to the host immune response to COVID-19

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Salvatore Sciacchitano ◽  
Andrea Sacconi ◽  
Claudia De Vitis ◽  
Giovanni Blandino ◽  
Giulia Piaggio ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Severe Disease ◽  
Host Immune Response ◽  
Severe Form ◽  
Ras Gene ◽  
Peripheral Blood Mononuclear ◽  
Ras Genes

AbstractRas gene family members play a relevant role in cancer, especially when they are mutated. However, they may play additional roles in other conditions beside cancer. We performed gene expression analysis using the NanoString PanCancer IO 360 panel in the peripheral blood mononuclear cell (PBMC) of six COVID-19 patients and we found that H-Ras gene was significantly upregulated, while both K-Ras and N-Ras genes were downregulated. In particular, H-Ras gene upregulation was more evident in COVID-19 patients with a more severe disease. We compared our results with those obtained by analyzing two different and independent datasets, including a total of 53 COVID-19 patients, in which the gene expression analysis was performed using the Immunology_V2 panel. Comparative analysis of the H-Ras gene expression in these patients confirmed our preliminary results. In both of them, in fact, we were able to confirm the upregulation of the expression of the H-Ras gene. The exact role of this specific upregulation of the H-Ras gene in response to SARS-CoV-2 infection and its possible role in cancer still remains to be elucidated. In conclusion, H-Ras gene participates to the host immune response to SARS-CoV-2 virus infection, especially in patients affected by the most severe form of the COVID-19.

scholarly journals Transcriptional and morphological profiling of parvalbumin interneuron subpopulations in the mouse hippocampus

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lin Que ◽  
David Lukacsovich ◽  
Wenshu Luo ◽  
Csaba Földy
Keyword(s):  
Large Scale ◽  
Cell Types ◽  
Rna Seq ◽  
Neuronal Identity ◽  
Parvalbumin Interneurons ◽  
Different Types ◽  
Parvalbumin Interneuron ◽  
Cam Profile ◽  
Developmental Domains

AbstractThe diversity reflected by >100 different neural cell types fundamentally contributes to brain function and a central idea is that neuronal identity can be inferred from genetic information. Recent large-scale transcriptomic assays seem to confirm this hypothesis, but a lack of morphological information has limited the identification of several known cell types. In this study, we used single-cell RNA-seq in morphologically identified parvalbumin interneurons (PV-INs), and studied their transcriptomic states in the morphological, physiological, and developmental domains. Overall, we find high transcriptomic similarity among PV-INs, with few genes showing divergent expression between morphologically different types. Furthermore, PV-INs show a uniform synaptic cell adhesion molecule (CAM) profile, suggesting that CAM expression in mature PV cells does not reflect wiring specificity after development. Together, our results suggest that while PV-INs differ in anatomy and in vivo activity, their continuous transcriptomic and homogenous biophysical landscapes are not predictive of these distinct identities.

scholarly journals Integration of tumor inflammation, cell proliferation, and traditional biomarkers improves prediction of immunotherapy resistance and response

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Sarabjot Pabla ◽  
R. J. Seager ◽  
Erik Van Roey ◽  
Shuang Gao ◽  
Carrie Hoefer ◽  
...  
Keyword(s):  
Immune Response ◽  
Cell Proliferation ◽  
Cell Activation ◽  
Response Rate ◽  
Checkpoint Inhibitors ◽  
Host Immune Response ◽  
Gene Signature ◽  
B Cell Activation ◽  
Rna Seq ◽  
Multiple Tumor

Abstract Background Contemporary to the rapidly evolving landscape of cancer immunotherapy is the equally changing understanding of immune tumor microenvironments (TMEs) which is crucial to the success of these therapies. Their reliance on a robust host immune response necessitates clinical grade measurements of immune TMEs at diagnosis. In this study, we describe a stable tumor immunogenic profile describing immune TMEs in multiple tumor types with ability to predict clinical benefit from immune checkpoint inhibitors (ICIs). Methods A tumor immunogenic signature (TIGS) was derived from targeted RNA-sequencing (RNA-seq) and gene expression analysis of 1323 clinical solid tumor cases spanning 35 histologies using unsupervised analysis. TIGS correlation with ICI response and survival was assessed in a retrospective cohort of NSCLC, melanoma and RCC tumor blocks, alone and combined with TMB, PD-L1 IHC and cell proliferation biomarkers. Results Unsupervised clustering of RNA-seq profiles uncovered a 161 gene signature where T cell and B cell activation, IFNg, chemokine, cytokine and interleukin pathways are over-represented. Mean expression of these genes produced three distinct TIGS score categories: strong (n = 384/1323; 29.02%), moderate (n = 354/1323; 26.76%), and weak (n = 585/1323; 44.22%). Strong TIGS tumors presented an improved ICI response rate of 37% (30/81); with highest response rate advantage occurring in NSCLC (ORR = 36.6%; 16/44; p = 0.051). Similarly, overall survival for strong TIGS tumors trended upward (median = 25 months; p = 0.19). Integrating the TIGS score categories with neoplastic influence quantified via cell proliferation showed highly proliferative and strong TIGS tumors correlate with significantly higher ICI ORR than poorly proliferative and weak TIGS tumors [14.28%; p = 0.0006]. Importantly, we noted that strong TIGS and highly [median = not achieved; p = 0.025] or moderately [median = 16.2 months; p = 0.025] proliferative tumors had significantly better survival compared to weak TIGS, highly proliferative tumors [median = 7.03 months]. Importantly, TIGS discriminates subpopulations of potential ICI responders that were considered negative for response by TMB and PD-L1. Conclusions TIGS is a comprehensive and informative measurement of immune TME that effectively characterizes host immune response to ICIs in multiple tumors. The results indicate that when combined with PD-L1, TMB and cell proliferation, TIGS provides greater context of both immune and neoplastic influences on the TME for implementation into clinical practice.

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