scholarly journals Optogenetic perturbations of RNA expression in tissue space

2021 ◽  
Author(s):  
Ivano Legnini ◽  
Lisa Emmenegger ◽  
Ricardo Wurmus ◽  
Alessandra Zappulo ◽  
Anna Oliveras Martinez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Sonic Hedgehog ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Spatial Location ◽  
Knock Down ◽  
Spatial Domains ◽  
Tissue Space ◽  
Spatial Locations

AbstractQuantifying gene expression in space, for example by spatial transcriptomics, is essential for describing the biology of cells and their interactions in complex tissues. Perturbation experiments, at single-cell resolution and conditional on both space and time, are necessary for dissecting the molecular mechanisms of these interactions. To this aim, we combined optogenetics and CRISPR technologies to activate or knock-down RNA of target genes, at single-cell resolution and in programmable spatial patterns. As a proof of principle, we optogenetically induced Sonic Hedgehog (SHH) signaling at a distinct spatial location within human neural organoids. This robustly induced known SHH spatial domains of gene expression – cell-autonomously and across the entire organoid. In principle, our approach can be used to induce or knock down RNAs from any gene of interest in specific spatial locations or patterns of complex biological systems.

scholarly journals The Integrated RNA Landscape of Renal Preconditioning against Ischemia-Reperfusion Injury

2020 ◽  
Vol 31 (4) ◽  
pp. 716-730 ◽  
Author(s):  
Marc Johnsen ◽  
Torsten Kubacki ◽  
Assa Yeroslaviz ◽  
Martin Richard Späth ◽  
Jannis Mörsdorf ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reperfusion Injury ◽  
Caloric Restriction ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Ischemia Reperfusion Injury ◽  
Ischemia Reperfusion ◽  
Hypoxic Preconditioning ◽  
Preventive Strategies ◽  
Gene Expression Signatures

BackgroundAlthough AKI lacks effective therapeutic approaches, preventive strategies using preconditioning protocols, including caloric restriction and hypoxic preconditioning, have been shown to prevent injury in animal models. A better understanding of the molecular mechanisms that underlie the enhanced resistance to AKI conferred by such approaches is needed to facilitate clinical use. We hypothesized that these preconditioning strategies use similar pathways to augment cellular stress resistance.MethodsTo identify genes and pathways shared by caloric restriction and hypoxic preconditioning, we used RNA-sequencing transcriptome profiling to compare the transcriptional response with both modes of preconditioning in mice before and after renal ischemia-reperfusion injury.ResultsThe gene expression signatures induced by both preconditioning strategies involve distinct common genes and pathways that overlap significantly with the transcriptional changes observed after ischemia-reperfusion injury. These changes primarily affect oxidation-reduction processes and have a major effect on mitochondrial processes. We found that 16 of the genes differentially regulated by both modes of preconditioning were strongly correlated with clinical outcome; most of these genes had not previously been directly linked to AKI.ConclusionsThis comparative analysis of the gene expression signatures in preconditioning strategies shows overlapping patterns in caloric restriction and hypoxic preconditioning, pointing toward common molecular mechanisms. Our analysis identified a limited set of target genes not previously known to be associated with AKI; further study of their potential to provide the basis for novel preventive strategies is warranted. To allow for optimal interactive usability of the data by the kidney research community, we provide an online interface for user-defined interrogation of the gene expression datasets (http://shiny.cecad.uni-koeln.de:3838/IRaP/).

MO262THE SINGLE-CELL TRANSCRIPTOMICS OF HUMAN IGA NEPHROPATHY

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Yong Zhong ◽  
Xiangcheng Xiao
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Signaling Pathways ◽  
Iga Nephropathy ◽  
Molecular Mechanisms ◽  
Mesangial Cells ◽  
Therapeutic Targets ◽  
Cell Types ◽  
Receptor Crosstalk ◽  
Overt Proteinuria

Abstract Background and Aims The exact molecular mechanisms underlying IgA nephropathy (IgAN) remains incompletely defined. Therefore, it is necessary to further elucidate the mechanism of IgA nephropathy and find novel therapeutic targets. Method Single-cell RNA sequencing (scRNA-seq) was applied to kidney biopsies from 4 IgAN and 1 control subjects to define the transcriptomic landscape at the single-cell resolution. Unsupervised clustering analysis of kidney specimens was used to identify distinct cell clusters. Differentially expressed genes and potential signaling pathways involved in IgAN were also identified. Results Our analysis identified 14 cell subsets in kidney biopsies from IgAN patients, and analyzed changing gene expression in distinct renal cell types. We found increased mesangial expression of several novel genes including MALAT1, GADD45B, SOX4 and EDIL3, which were related to proliferation and matrix accumulation and have not been reported in IgAN previously. The overexpressed genes in tubule cells of IgAN were mainly enriched in inflammatory pathways including TNF signaling, IL-17 signaling and NOD-like receptor signaling. Moreover, the receptor-ligand crosstalk analysis revealed potential interactions between mesangial cells and other cells in IgAN. Specifically, IgAN with overt proteinuria displayed elevated genes participating in several signaling pathways which may be involved in pathogenesis of progression of IgAN. Conclusion The comprehensive analysis of kidney biopsy specimen demonstrated different gene expression profile, potential pathologic ligand-receptor crosstalk, signaling pathways in human IgAN. These results offer new insight into pathogenesis and identify new therapeutic targets for patients with IgA nephropathy.

scholarly journals Repurposing of KLF5 activates a cell cycle signature during the progression from a precursor state to Oesophageal Adenocarcinoma

2020 ◽  
Author(s):  
Connor Rogerson ◽  
Samuel Ogden ◽  
Edward Britton ◽  
Yeng Ang ◽  
Andrew D. Sharrocks ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Prognostic Significance ◽  
Gene Expression Signature ◽  
Chromatin Accessibility ◽  
Oesophageal Adenocarcinoma ◽  
Cell Cycle Gene ◽  
A Cell

AbstractOesophageal adenocarcinoma (OAC) is one of the most common causes of cancer deaths and yet compared to other common cancers, we know relatively little about the underlying molecular mechanisms. Barrett’s oesophagus (BO) is the only known precancerous precursor to OAC, but our understanding about the specific events leading to OAC development is limited. Here, we have integrated gene expression and chromatin accessibility profiles of human biopsies of BO and OAC and identified a strong cell cycle gene expression signature in OAC compared to BO. Through analysing associated chromatin accessibility changes, we have implicated the transcription factor KLF5 in the transition from BO to OAC. Importantly, we show that KLF5 expression is unchanged during this transition, but instead, KLF5 is redistributed across chromatin in OAC cells to directly regulate cell cycle genes specifically in OAC. Our findings have potential prognostic significance as the survival of patients with high expression of KLF5 target genes is significantly lower. We have provided new insights into the gene expression networks in OAC and the mechanisms behind progression to OAC, chiefly the repurposing of KLF5 for novel regulatory activity in OAC.

Circulating melanoma cells isolated from clinical blood samples and characterized by full-length mRNA sequencing at single-cell level.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 10539-10539 ◽  
Author(s):  
Yu-Chieh Wang ◽  
Daniel Ramskold ◽  
Shujun Luo ◽  
Robin Li ◽  
Qiaolin Deng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Melanoma Cells ◽  
Clinical Samples ◽  
Single Cell Level ◽  
Cell Level ◽  
Blood Samples

10539 Background: Melanoma is the most aggressive type of skin cancer. Late-stage melanoma is highly metastatic and currently lacks effective treatment. This discouraging clinical observation highlights the need for a better understanding of the molecular mechanisms underlying melanoma initiation and progression and for developing new therapeutic approaches based on novel targets. Although genome-wide transcriptome analyses have been frequently used to study molecular alterations in clinical samples, it has been technically challenging to obtain the transcriptomic profiles at single-cell level. Methods: Using antibody-mediated magnetic activated cell separation (MACS), we isolated and individualized putative circulating melanoma cells (CMCs) from the blood samples of the melanoma patients at advance stages. The transcriptomic analysis based on a novel and robust mRNA-Seq protocol (Smart-Seq) was established and applied to the putative CMCs for single-cell profiling. Results: We have discovered distinct gene expression patterns, including new putative markers for CMCs. Meanwhile, the gene expression profiles derived of the CMC candidates isolated from the patient’s blood samples are closely-related to the expression profiles of other cells originated from human melanocytes, including normal melanocytes in primary culture and melanoma cell lines. Compared with existing methods, Smart-Seq has improved read coverage across transcripts, which provides advantage for better analyzing transcript isoforms and SNPs. Conclusions: Our results suggest that the techniques developed in this research for cell isolation and transcriptomic analyses can potentially be used for addressing many biological and clinical questions requiring genomewide transcriptome profiling in rare cells.

Gene Expression Analysis on the Early Development of Pig Embryos Exposed to Malathion

2007 ◽  
Vol 26 (2) ◽  
pp. 143-149 ◽  
Author(s):  
Zayil Salazar ◽  
Yvonne Ducolomb ◽  
Miguel Betancourt ◽  
Edmundo Bonilla ◽  
Leticia Cortés ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Hypothetical Protein ◽  
Cdna Libraries ◽  
Mhc I ◽  
Vitro Fertilization ◽  
Embryo Cells ◽  
Gene Expression Alterations

Malathion is a widely used pesticide and there is evidence that it could alter mammal’s germ and somatic cells, as well as cell lines. There are not enough studies showing how the nonacute malathion doses affect gene expression. This study analyzes gene expression alterations in pig morular embryos exposed in vitro , for 96 h, to several malathion concentrations after in vitro fertilization. cDNA libraries of isolated morular embryos were created and differential screenings performed to identify target genes. Seven clones were certainly identified. Genes related to mitochondrial metabolism as cytochrome c subunits I and III, nuclear genes such as major histocompatibility complex I (MHC I), and a hypothetical protein related with a splicing factor were the target of malathion’s deregulation effect. The widespread use of malathion as a pesticide should be regarded with reproductive implications and more detailed analysis would yield more about molecular mechanisms of malathion injury on embryo cells.

scholarly journals Human Sterol Regulatory Element-Binding Protein 1a Contributes Significantly to Hepatic Lipogenic Gene Expression

2015 ◽  
Vol 35 (2) ◽  
pp. 803-815 ◽  
Author(s):  
Andreas Bitter ◽  
Andreas K. Nüssler ◽  
Wolfgang E. Thasler ◽  
Kathrin Klein ◽  
Ulrich M. Zanger ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Liver ◽  
Target Genes ◽  
Binding Protein ◽  
Regulatory Element ◽  
Lipogenic Gene ◽  
Knock Down ◽  
Lipogenic Gene Expression ◽  
Element Binding Protein ◽  
Sterol Regulatory Element

Background/Aims: Sterol regulatory element-binding protein (SREBP) 1, the master regulator of lipogenesis, was shown to be associated with non-alcoholic fatty liver disease, which is attributed to its major isoform SREBP1c. Based on studies in mice, the minor isoform SREBP1a is regarded as negligible for hepatic lipogenesis. This study aims to elucidate the expression and functional role of SREBP1a in human liver. Methods: mRNA expression of both isoforms was quantified in cohorts of human livers and primary human hepatocytes. Hepatocytes were treated with PF-429242 to inhibit the proteolytic activation of SREBP precursor protein. SREBP1a-specifc and pan-SREBP1 knock-down were performed by transfection of respective siRNAs. Lipogenic SREBP-target gene expression was analyzed by real-time RT-PCR. Results: In human liver, SREBP1a accounts for up to half of the total SREBP1 pool. Treatment with PF-429242 indicated SREBP-dependent auto-regulation of SREBP1a, which however was much weaker than of SREBP1c. SREBP1a-specifc knock-down also reduced significantly the expression of SREBP1c and of SREBP-target genes. Regarding most SREBP-target genes, simultaneous knock-down of both isoforms resulted in effects of only similar extent as SREBP1a-specific knock-down. Conclusion: We here showed that SREBP1a is significantly contributing to the human hepatic SREBP1 pool and has a share in human hepatic lipogenic gene expression.

scholarly journals Intrauterine calorie restriction affects placental DNA methylation and gene expression

2013 ◽  
Vol 45 (14) ◽  
pp. 565-576 ◽  
Author(s):  
Pao-Yang Chen ◽  
Amit Ganguly ◽  
Liudmilla Rubbi ◽  
Luz D. Orozco ◽  
Marco Morselli ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Chronic Diseases ◽  
Calorie Restriction ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Specific Effects ◽  
Differentially Methylated Genes ◽  
Critical Organ ◽  
Successive Generations

Maternal nutrient restriction causes the development of adult onset chronic diseases in the intrauterine growth restricted (IUGR) fetus. Investigations in mice have shown that either protein or calorie restriction during pregnancy leads to glucose intolerance, increased fat mass, and hypercholesterolemia in adult male offspring. Some of these phenotypes are shown to persist in successive generations. The molecular mechanisms underlying IUGR remain unclear. The placenta is a critical organ for mediating changes in the environment and the development of embryos. To shed light on molecular mechanisms that might affect placental responses to differing environments we examined placentas from mice that had been exposed to different diets. We measured gene expression and whole genome DNA methylation in both male and female placentas of mice exposed to either caloric restriction or ad libitum diets. We observed several differentially expressed pathways associated with IUGR phenotypes and, most importantly, a significant decrease in the overall methylation between these groups as well as sex-specific effects that are more pronounced in males. In addition, a set of significantly differentially methylated genes that are enriched for known imprinted genes were identified, suggesting that imprinted loci may be particularly susceptible to diet effects. Lastly, we identified several differentially methylated microRNAs that target genes associated with immunological, metabolic, gastrointestinal, cardiovascular, and neurological chronic diseases, as well as genes responsible for transplacental nutrient transfer and fetal development.

scholarly journals dynDeepDRIM: a dynamic deep learning model to infer direct regulatory interactions using single cell time-course gene expression data

2021 ◽  
Author(s):  
Yu Xu ◽  
Jiaxing Chen ◽  
Aiping Lyu ◽  
William K Cheung ◽  
Lu Zhang
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Gene Expression Data ◽  
Time Course ◽  
Target Genes ◽  
Neighborhood Context ◽  
Specific Gene ◽  
Expression Data ◽  
Regulatory Interactions ◽  
Gene Functions

Time-course single-cell RNA sequencing (scRNA-seq) data have been widely applied to reconstruct the cell-type-specific gene regulatory networks by exploring the dynamic changes of gene expression between transcription factors (TFs) and their target genes. The existing algorithms were commonly designed to analyze bulk gene expression data and could not deal with the dropouts and cell heterogeneity in scRNA-seq data. In this paper, we developed dynDeepDRIM that represents gene pair joint expression as images and considers the neighborhood context to eliminate the transitive interactions. dynDeepDRIM integrated the primary image, neighbor images with time-course into a four-dimensional tensor and trained a convolutional neural network to predict the direct regulatory interactions between TFs and genes. We evaluated the performance of dynDeepDRIM on five time-course gene expression datasets. dynDeepDRIM outperformed the state-of-the-art methods for predicting TF-gene direct interactions and gene functions. We also observed gene functions could be better performed if more neighbor images were involved.

scholarly journals Transcriptomics identifies STAT3 as a key regulator of hippocampal gene expression and anhedonia during withdrawal from chronic alcohol exposure

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wei-Yang Chen ◽  
Hu Chen ◽  
Kana Hamada ◽  
Eleonora Gatta ◽  
Ying Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alcohol Drinking ◽  
Alcohol Withdrawal ◽  
Drug Targets ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Alcohol Exposure ◽  
Immune Gene ◽  
Chronic Alcohol ◽  
Chronic Alcohol Exposure

AbstractAlcohol use disorder (AUD) is highly comorbid with depression. Withdrawal from chronic alcohol drinking results in depression and understanding brain molecular mechanisms that drive withdrawal-related depression is important for finding new drug targets to treat these comorbid conditions. Here, we performed RNA sequencing of the rat hippocampus during withdrawal from chronic alcohol drinking to discover key signaling pathways involved in alcohol withdrawal-related depressive-like behavior. Data were analyzed by weighted gene co-expression network analysis to identify several modules of co-expressed genes that could have a common underlying regulatory mechanism. One of the hub, or highly interconnected, genes in module 1 that increased during alcohol withdrawal was the transcription factor, signal transducer and activator of transcription 3 (Stat3), a known regulator of immune gene expression. Total and phosphorylated (p)STAT3 protein levels were also increased in the hippocampus during withdrawal after chronic alcohol exposure. Further, pSTAT3 binding was enriched at the module 1 genes Gfap, Tnfrsf1a, and Socs3 during alcohol withdrawal. Notably, pSTAT3 and its target genes were elevated in the postmortem hippocampus of human subjects with AUD when compared with control subjects. To determine the behavioral relevance of STAT3 activation during alcohol withdrawal, we treated rats with the STAT3 inhibitor stattic and tested for sucrose preference as a measure of anhedonia. STAT3 inhibition alleviated alcohol withdrawal-induced anhedonia. These results demonstrate activation of STAT3 signaling in the hippocampus during alcohol withdrawal in rats and in human AUD subjects, and suggest that STAT3 could be a therapeutic target for reducing comorbid AUD and depression.

scholarly journals Gene regulatory network reconstruction using single-cell RNA sequencing of barcoded genotypes in diverse environments

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Christopher A Jackson ◽  
Dayanne M Castro ◽  
Giuseppe-Antonio Saldi ◽  
Richard Bonneau ◽  
David Gresham
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Gene Regulatory Network ◽  
Gene Regulatory Networks ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Target Genes ◽  
Single Cell Rna Sequencing ◽  
Gene Regulatory

Understanding how gene expression programs are controlled requires identifying regulatory relationships between transcription factors and target genes. Gene regulatory networks are typically constructed from gene expression data acquired following genetic perturbation or environmental stimulus. Single-cell RNA sequencing (scRNAseq) captures the gene expression state of thousands of individual cells in a single experiment, offering advantages in combinatorial experimental design, large numbers of independent measurements, and accessing the interaction between the cell cycle and environmental responses that is hidden by population-level analysis of gene expression. To leverage these advantages, we developed a method for scRNAseq in budding yeast (Saccharomyces cerevisiae). We pooled diverse transcriptionally barcoded gene deletion mutants in 11 different environmental conditions and determined their expression state by sequencing 38,285 individual cells. We benchmarked a framework for learning gene regulatory networks from scRNAseq data that incorporates multitask learning and constructed a global gene regulatory network comprising 12,228 interactions.

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