Visualization of Endogenous Transcription Factors in Single Cells Using an Antibody Electroporation-Based Imaging Approach

2019 ◽  
pp. 209-221
Author(s):  
Sascha Conic ◽  
Dominique Desplancq ◽  
Alexia Ferrand ◽  
Nacho Molina ◽  
Etienne Weiss ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Single Cells ◽  
Imaging Approach

Reduction in gene expression noise by targeted increase in accessibility at gene loci

2021 ◽  
Vol 118 (42) ◽  
pp. e2018640118
Author(s):  
LaTasha C. R. Fraser ◽  
Ryan J. Dikdan ◽  
Supravat Dey ◽  
Abhyudai Singh ◽  
Sanjay Tyagi
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Single Molecule ◽  
Single Cells ◽  
Global Changes ◽  
Messenger Rnas ◽  
Histone Acetyl Transferase ◽  
Gene Expression Noise ◽  
Expression Noise ◽  
Eukaryotic Genes

Many eukaryotic genes are expressed in randomly initiated bursts that are punctuated by periods of quiescence. Here, we show that the intermittent access of the promoters to transcription factors through relatively impervious chromatin contributes to this “noisy” transcription. We tethered a nuclease-deficient Cas9 fused to a histone acetyl transferase at the promoters of two endogenous genes in HeLa cells. An assay for transposase-accessible chromatin using sequencing showed that the activity of the histone acetyl transferase altered the chromatin architecture locally without introducing global changes in the nucleus and rendered the targeted promoters constitutively accessible. We measured the gene expression variability from the gene loci by performing single-molecule fluorescence in situ hybridization against mature messenger RNAs (mRNAs) and by imaging nascent mRNA molecules present at active gene loci in single cells. Because of the increased accessibility of the promoter to transcription factors, the transcription from two genes became less noisy, even when the average levels of expression did not change. In addition to providing evidence for chromatin accessibility as a determinant of the noise in gene expression, our study offers a mechanism for controlling gene expression noise which is otherwise unavoidable.

scholarly journals Genomic Architecture of Cells in Tissues (GeACT): Study of Human Mid-gestation Fetus

2020 ◽  
Author(s):  
Feng Tian ◽  
Fan Zhou ◽  
Xiang Li ◽  
Wenping Ma ◽  
Honggui Wu ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Human Cell ◽  
Expression Profiles ◽  
Single Cells ◽  
Cell Types ◽  
List Type ◽  
Cell Type ◽  
Genomic Architecture ◽  
Gene Modules

SummaryBy circumventing cellular heterogeneity, single cell omics have now been widely utilized for cell typing in human tissues, culminating with the undertaking of human cell atlas aimed at characterizing all human cell types. However, more important are the probing of gene regulatory networks, underlying chromatin architecture and critical transcription factors for each cell type. Here we report the Genomic Architecture of Cells in Tissues (GeACT), a comprehensive genomic data base that collectively address the above needs with the goal of understanding the functional genome in action. GeACT was made possible by our novel single-cell RNA-seq (MALBAC-DT) and ATAC-seq (METATAC) methods of high detectability and precision. We exemplified GeACT by first studying representative organs in human mid-gestation fetus. In particular, correlated gene modules (CGMs) are observed and found to be cell-type-dependent. We linked gene expression profiles to the underlying chromatin states, and found the key transcription factors for representative CGMs.HighlightsGenomic Architecture of Cells in Tissues (GeACT) data for human mid-gestation fetusDetermining correlated gene modules (CGMs) in different cell types by MALBAC-DTMeasuring chromatin open regions in single cells with high detectability by METATACIntegrating transcriptomics and chromatin accessibility to reveal key TFs for a CGM

scholarly journals Leveraging high-powered RNA-Seq datasets to improve inference of regulatory activity in single-cell RNA-Seq data

2019 ◽  
Author(s):  
Ning Wang ◽  
Andrew E. Teschendorff
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Cell Fate ◽  
Regulatory Networks ◽  
Large Scale ◽  
Single Cells ◽  
Differential Expression Analysis ◽  
Dropout Rate ◽  
Rna Seq ◽  
Regulatory Activity

AbstractInferring the activity of transcription factors in single cells is a key task to improve our understanding of development and complex genetic diseases. This task is, however, challenging due to the relatively large dropout rate and noisy nature of single-cell RNA-Seq data. Here we present a novel statistical inference framework called SCIRA (Single Cell Inference of Regulatory Activity), which leverages the power of large-scale bulk RNA-Seq datasets to infer high-quality tissue-specific regulatory networks, from which regulatory activity estimates in single cells can be subsequently obtained. We show that SCIRA can correctly infer regulatory activity of transcription factors affected by high technical dropouts. In particular, SCIRA can improve sensitivity by as much as 70% compared to differential expression analysis and current state-of-the-art methods. Importantly, SCIRA can reveal novel regulators of cell-fate in tissue-development, even for cell-types that only make up 5% of the tissue, and can identify key novel tumor suppressor genes in cancer at single cell resolution. In summary, SCIRA will be an invaluable tool for single-cell studies aiming to accurately map activity patterns of key transcription factors during development, and how these are altered in disease.

scholarly journals Enhancer priming enables fast and sustained transcriptional responses to Notch signaling

2018 ◽  
Author(s):  
Julia Falo-Sanjuan ◽  
Nicholas C Lammers ◽  
Hernan G Garcia ◽  
Sarah Bray
Keyword(s):  
Transcription Factors ◽  
Dynamic Response ◽  
Notch Signaling ◽  
Real Time ◽  
Single Cells ◽  
Transcriptional Responses ◽  
Sustained Activity ◽  
Developmental Signaling ◽  
Cellular Context ◽  
Nascent Transcripts

SummaryInformation from developmental signaling pathways must be accurately decoded to generate transcriptional outcomes. In the case of Notch, the intracellular domain (NICD) transduces the signal directly to the nucleus. How enhancers decipher NICD in the real time of developmental decisions is not known. Using the MS2/MCP system to visualize nascent transcripts in single cells in Drosophila embryos we reveal how two target enhancers read Notch activity to produce synchronized and sustained profiles of transcription. By manipulating the levels of NICD and altering specific motifs within the enhancers we uncover two key principles. First, increased NICD levels alter transcription by increasing duration rather than frequency of transcriptional bursts. Second, priming of enhancers by tissue-specific transcription factors is required for NICD to confer synchronized and sustained activity; in their absence, transcription is stochastic and bursty. The dynamic response of an individual enhancer to NICD thus differs depending on the cellular context.

scholarly journals Phenotypic convergence in the brain: distinct transcription factors regulate common terminal neuronal characters

2018 ◽  
Author(s):  
Nikos Konstantinides ◽  
Katarina Kapuralin ◽  
Chaimaa Fadil ◽  
Luendreo Barboza ◽  
Rahul Satija ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Large Scale ◽  
Single Cells ◽  
Deep Understanding ◽  
Cell Types ◽  
Marker Genes ◽  
Cell Type ◽  
Functional Specification ◽  
Phenotypic Convergence

SummaryTranscription factors regulate the molecular, morphological, and physiological characters of neurons and generate their impressive cell type diversity. To gain insight into general principles that govern how transcription factors regulate cell type diversity, we used large-scale single-cell mRNA sequencing to characterize the extensive cellular diversity in the Drosophila optic lobes. We sequenced 55,000 single optic lobe neurons and glia and assigned them to 52 clusters of transcriptionally distinct single cells. We validated the clustering and annotated many of the clusters using RNA sequencing of characterized FACS-sorted single cell types, as well as marker genes specific to given clusters. To identify transcription factors responsible for inducing specific terminal differentiation features, we used machine-learning to generate a ‘random forest’ model. The predictive power of the model was confirmed by showing that two transcription factors expressed specifically in cholinergic (apterous) and glutamatergic (traffic-jam) neurons are necessary for the expression of ChAT and VGlut in many, but not all, cholinergic or glutamatergic neurons, respectively. We used a transcriptome-wide approach to show that the same terminal characters, including but not restricted to neurotransmitter identity, can be regulated by different transcription factors in different cell types, arguing for extensive phenotypic convergence. Our data provide a deep understanding of the developmental and functional specification of a complex brain structure.

Simultaneous measurement of intracellular pH and Ca2+ in insulin-secreting cells by spectral imaging microscopy

1996 ◽  
Vol 270 (5) ◽  
pp. C1438-C1446 ◽  
Author(s):  
R. Martinez-Zaguilan ◽  
M. W. Gurule ◽  
R. M. Lynch
Keyword(s):  
Intracellular Ph ◽  
Single Cells ◽  
Ion Homeostasis ◽  
Spectral Imaging ◽  
Charge Coupled Device ◽  
Fura 2 ◽  
Imaging Approach ◽  
Insulin Secreting Cells ◽  
A Cell ◽  
Cytosolic Acidification

Described is a microscopic spectral imaging approach to monitor pH and Ca2+ simultaneously from combined spectra of multiple ion indicators. Emitted light from a cell is focused onto a grating spectrograph and spectra are imaged with a cooled charge-coupled device camera. The combined spectral output of fura 2 and SNARF-1 was analyzed to follow changes in intracellular Ca2+ concentration ([Ca2+]i) and intracellular pH (pHi) simultaneously and to correct the Ca2+ signal for concurrent changes in pHi. Responses of individual hamster insulinoma (HIT-T15) cells to effectors of ion homeostasis were heterogeneous. Treatment with NH4Cl increased pHi and transiently increased [Ca2+]i. Removal of NH4Cl induced cytosolic acidification concomitant with either no change or sustained increases in [Ca2-]i. Glucose treatment generally resulted in rapid and sustained increases in both [Ca2+]i and pHi but also heterogeneous pHi and [Ca2+]i responses. Corrections of the fura 2 signal for pH were important for following Ca2+ transitions elicited by NH4Cl but were less important for glucose-induced responses. The spectral imaging microscope provides a sensitive method for simultaneous measurements of pHi and [Ca2+]i in single cells.

scholarly journals Single cells and transposable element heterogeneity in stem cells and development

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Andrew P. Hutchins
Keyword(s):  
Stem Cells ◽  
Transcription Factors ◽  
Single Cell ◽  
Human Disease ◽  
Single Cells ◽  
Chromatin Modifications ◽  
Single Cell Sequencing ◽  
Insight Into ◽  
Expression And Activity ◽  
Host Complex

AbstractRecent innovations in single cell sequencing-based technologies are shining a light on the heterogeneity of cellular populations in unprecedented detail. However, several cellular aspects are currently underutilized in single cell studies. One aspect is the expression and activity of transposable elements (TEs). TEs are selfish sequences of DNA that can replicate, and have been wildly successful in colonizing genomes. However, most TEs are mutated, fragmentary and incapable of transposition, yet they are actively bound by multiple transcription factors, host complex patterns of chromatin modifications, and are expressed in mRNAs as part of the transcriptome in both normal and diseased states. The contribution of TEs to development and cellular function remains unclear, and the routine inclusion of TEs in single cell sequencing analyses will potentially lead to insight into stem cells, development and human disease.

scholarly journals Density Fluctuations Yield Distinct Growth and Fitness Effects in Single Bacteria

2021 ◽  
Author(s):  
Shahla Nemati ◽  
Abhyudai Singh ◽  
Scott Dhuey ◽  
Armando McDonald ◽  
Daniel Weinreich ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Density Fluctuations ◽  
Accumulation Rates ◽  
Fitness Effects ◽  
Unknown Density ◽  
Escherichia Coli Cells ◽  
Cell Reproduction ◽  
Imaging Approach ◽  
Biochemical Production

Single-cells grow by increasing their biomass and size. Here, we report that while mass and size accumulation rates of single Escherichia coli cells are exponential, their density fluctuates during growth. As such, the rates of mass and size accumulation of a single-cell are generally not the same, but rather cells differentiate into increasing one rate with respect to the other. This differentiation yields a previously unknown density homeostasis mechanism, which we support mathematically. Further, growth differentiation challenges ongoing efforts to predict single-cell reproduction rates (or fitness-levels), through the accumulation rates of size or mass. In contrast, we observe that density fluctuations can predict fitness, with only high fitness individuals existing in the high density fluctuation regime. We detail our imaging approach and the invisible microfluidic arrays that critically enabled increased precision and throughput. Biochemical production, infections, and natural communities start from few, growing, cells, thus, underscoring the significance of density-fluctuations when considering non-genetic variability.

scholarly journals SCENIC: Single-cell regulatory network inference and clustering

2017 ◽  
Author(s):  
Sara Aibar ◽  
Carmen Bravo González-Blas ◽  
Thomas Moerman ◽  
Jasper Wouters ◽  
Vân Anh Huynh-Thu ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Regulatory Network ◽  
Network Inference ◽  
Target Genes ◽  
Single Cells ◽  
State Transitions ◽  
Rna Seq ◽  
Cell State ◽  
Gene Regulatory

AbstractSingle-cell RNA-seq allows building cell atlases of any given tissue and infer the dynamics of cellular state transitions during developmental or disease trajectories. Both the maintenance and transitions of cell states are encoded by regulatory programs in the genome sequence. However, this regulatory code has not yet been exploited to guide the identification of cellular states from single-cell RNA-seq data. Here we describe a computational resource, called SCENIC (Single Cell rEgulatory Network Inference and Clustering), for the simultaneous reconstruction of gene regulatory networks (GRNs) and the identification of stable cell states, using single-cell RNA-seq data. SCENIC outperforms existing approaches at the level of cell clustering and transcription factor identification. Importantly, we show that cell state identification based on GRNs is robust towards batch-effects and technical-biases. We applied SCENIC to a compendium of single-cell data from the mouse and human brain and demonstrate that the proper combinations of transcription factors, target genes, enhancers, and cell types can be identified. Moreover, we used SCENIC to map the cell state landscape in melanoma and identified a gene regulatory network underlying a proliferative melanoma state driven by MITF and STAT and a contrasting network controlling an invasive state governed by NFATC2 and NFIB. We further validated these predictions by showing that two transcription factors are predominantly expressed in early metastatic sentinel lymph nodes. In summary, SCENIC is the first method to analyze scRNA-seq data using a network-centric, rather than cell-centric approach. SCENIC is generic, easy to use, and flexible, and allows for the simultaneous tracing of genomic regulatory programs and the mapping of cellular identities emerging from these programs. Availability: SCENIC is available as an R workflow based on three new R/Bioconductor packages: GENIE3, RcisTarget and AUCell. As scalable alternative to GENIE3, we also provide GRNboost, paving the way towards the network analysis across millions of single cells.

scholarly journals Single-particle view of stress-promoters induction dynamics: an interplay between MAPK signaling, chromatin and transcription factors

2019 ◽  
Author(s):  
Victoria Wosika ◽  
Serge Pelet
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Environmental Changes ◽  
Osmotic Shock ◽  
Single Cells ◽  
Regulation Of Gene Expression ◽  
Mapk Signaling ◽  
Extracellular Signal ◽  
Mitogen Activated Protein ◽  
Transient Activity

AbstractPrecise regulation of gene expression in response to environmental changes is crucial for cell survival, adaptation and proliferation. In eukaryotic cells, extracellular signal integration is often carried out by Mitogen-Activated Protein Kinases (MAPK). Despite a robust MAPK signaling activity, downstream gene expression can display a great variability between single cells. Using a live mRNA reporter, we monitored the dynamics of transcription in Saccharomyces cerevisiae upon hyper-osmotic shock. The transient activity of the MAPK Hog1 opens a temporal window where stress-response genes can be activated. Here we show that the first minutes of Hog1 activity are essential to control the activation of a promoter. The chromatin repression on a locus slows down this transition and contributes to the variability in gene expression, while binding of transcription factors increases the level of transcription. However, soon after Hog1 activity peaks, negative regulators promote chromatin closure of the locus and transcription progressively stops.

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