scholarly journals Multicellular Models Bridging Intracellular Signaling and Gene Transcription to Population Dynamics

Processes ◽  
2018 ◽  
Vol 6 (11) ◽  
pp. 217 ◽  
Author(s):  
Mohammad Islam ◽  
Satyaki Roy ◽  
Sajal Das ◽  
Dipak Barua
Keyword(s):  
Single Cell ◽  
Gene Transcription ◽  
Intracellular Signaling ◽  
Message Passing Interface ◽  
Cell Model ◽  
Parallel Process ◽  
Biochemical Network ◽  
Scale Model ◽  
Bacterial Cells ◽  
Growth Environment

Cell signaling and gene transcription occur at faster time scales compared to cellular death, division, and evolution. Bridging these multiscale events in a model is computationally challenging. We introduce a framework for the systematic development of multiscale cell population models. Using message passing interface (MPI) parallelism, the framework creates a population model from a single-cell biochemical network model. It launches parallel simulations on a single-cell model and treats each stand-alone parallel process as a cell object. MPI mediates cell-to-cell and cell-to-environment communications in a server-client fashion. In the framework, model-specific higher level rules link the intracellular molecular events to cellular functions, such as death, division, or phenotype change. Cell death is implemented by terminating a parallel process, while cell division is carried out by creating a new process (daughter cell) from an existing one (mother cell). We first demonstrate these capabilities by creating two simple example models. In one model, we consider a relatively simple scenario where cells can evolve independently. In the other model, we consider interdependency among the cells, where cellular communication determines their collective behavior and evolution under a temporally evolving growth condition. We then demonstrate the framework’s capability by simulating a full-scale model of bacterial quorum sensing, where the dynamics of a population of bacterial cells is dictated by the intercellular communications in a time-evolving growth environment.

scholarly journals Multi-scale dynamical modelling of T-cell development from an early thymic progenitor state to lineage commitment

2019 ◽  
Author(s):  
Victor Olariu ◽  
Mary A. Yui ◽  
Pawel Krupinski ◽  
Wen Zhou ◽  
Julia Deichmann ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Single Molecule ◽  
Network Architecture ◽  
Cell Model ◽  
Core Gene ◽  
Scale Model ◽  
Environmental Signals ◽  
Multi Scale ◽  
Clonal Proliferation

AbstractThymic development of committed pro-T-cells from multipotent hematopoietic precursors offers a unique opportunity to dissect the molecular circuitry establishing cell identity in response to environmental signals. This transition encompasses programmed shutoff of stem/progenitor genes, upregulation of T-cell specification genes, extensive proliferation, and commitment after a delay. We have incorporated these factors, as well as new single cell gene expression and developmental kinetics data, into a three-level dynamic model of commitment based upon regulation of the commitment gene Bcl11b. The first level is a core gene regulatory network architecture determined by transcription factor perturbation data, the second a stochastically controlled epigenetic gate, and the third a proliferation model validated by growth and commitment kinetics measured at single-cell levels. Using expression values consistent with single molecule RNA-FISH measurements of key transcription factors, this single-cell model exhibits state switching consistent with measured population and clonal proliferation and commitment times. The resulting multi-scale model provides a powerful mechanistic framework for dissecting commitment dynamics.

scholarly journals Melanoma Single-Cell Biology in Experimental and Clinical Settings

2021 ◽  
Vol 10 (3) ◽  
pp. 506
Author(s):  
Hans Binder ◽  
Maria Schmidt ◽  
Henry Loeffler-Wirth ◽  
Lena Suenke Mortensen ◽  
Manfred Kunz
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Intracellular Signaling ◽  
Cell Biology ◽  
Immune Cell ◽  
Malignant Tumors ◽  
Checkpoint Inhibitor ◽  
Treatment Resistance ◽  
Resistance Mechanisms ◽  
Cellular Heterogeneity

Cellular heterogeneity is regarded as a major factor for treatment response and resistance in a variety of malignant tumors, including malignant melanoma. More recent developments of single-cell sequencing technology provided deeper insights into this phenomenon. Single-cell data were used to identify prognostic subtypes of melanoma tumors, with a special emphasis on immune cells and fibroblasts in the tumor microenvironment. Moreover, treatment resistance to checkpoint inhibitor therapy has been shown to be associated with a set of differentially expressed immune cell signatures unraveling new targetable intracellular signaling pathways. Characterization of T cell states under checkpoint inhibitor treatment showed that exhausted CD8+ T cell types in melanoma lesions still have a high proliferative index. Other studies identified treatment resistance mechanisms to targeted treatment against the mutated BRAF serine/threonine protein kinase including repression of the melanoma differentiation gene microphthalmia-associated transcription factor (MITF) and induction of AXL receptor tyrosine kinase. Interestingly, treatment resistance mechanisms not only included selection processes of pre-existing subclones but also transition between different states of gene expression. Taken together, single-cell technology has provided deeper insights into melanoma biology and has put forward our understanding of the role of tumor heterogeneity and transcriptional plasticity, which may impact on innovative clinical trial designs and experimental approaches.

scholarly journals Ca2+ Microdomains, Calcineurin and the Regulation of Gene Transcription

Cells ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 875
Author(s):  
Gerald Thiel ◽  
Tobias Schmidt ◽  
Oliver G. Rössler
Keyword(s):  
Transcription Factors ◽  
Protein Kinase ◽  
Protein Kinases ◽  
Gene Transcription ◽  
Intracellular Signaling ◽  
Second Messengers ◽  
Major Function ◽  
Surface Receptors ◽  
Dependent Protein

Ca2+ ions function as second messengers regulating many intracellular events, including neurotransmitter release, exocytosis, muscle contraction, metabolism and gene transcription. Cells of a multicellular organism express a variety of cell-surface receptors and channels that trigger an increase of the intracellular Ca2+ concentration upon stimulation. The elevated Ca2+ concentration is not uniformly distributed within the cytoplasm but is organized in subcellular microdomains with high and low concentrations of Ca2+ at different locations in the cell. Ca2+ ions are stored and released by intracellular organelles that change the concentration and distribution of Ca2+ ions. A major function of the rise in intracellular Ca2+ is the change of the genetic expression pattern of the cell via the activation of Ca2+-responsive transcription factors. It has been proposed that Ca2+-responsive transcription factors are differently affected by a rise in cytoplasmic versus nuclear Ca2+. Moreover, it has been suggested that the mode of entry determines whether an influx of Ca2+ leads to the stimulation of gene transcription. A rise in cytoplasmic Ca2+ induces an intracellular signaling cascade, involving the activation of the Ca2+/calmodulin-dependent protein phosphatase calcineurin and various protein kinases (protein kinase C, extracellular signal-regulated protein kinase, Ca2+/calmodulin-dependent protein kinases). In this review article, we discuss the concept of gene regulation via elevated Ca2+ concentration in the cytoplasm and the nucleus, the role of Ca2+ entry and the role of enzymes as signal transducers. We give particular emphasis to the regulation of gene transcription by calcineurin, linking protein dephosphorylation with Ca2+ signaling and gene expression.

Calibration of single-cell model parameters based on membrane resistance improves the accuracy of cardiac tissue simulations

2021 ◽  
pp. 101375
Author(s):  
Elnaz Pouranbarani ◽  
Lucas Arantes Berg ◽  
Rafael Sachetto Oliveira ◽  
Rodrigo Weber dos Santos ◽  
Anders Nygren
Keyword(s):  
Single Cell ◽  
Cardiac Tissue ◽  
Cell Model ◽  
Membrane Resistance ◽  
Model Parameters ◽  
Single Cell Model

scholarly journals Direct observation of frequency modulated transcription in single cells using light activation

eLife ◽  
2013 ◽  
Vol 2 ◽  
Author(s):  
Daniel R Larson ◽  
Christoph Fritzsch ◽  
Liang Sun ◽  
Xiuhau Meng ◽  
David S Lawrence ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Molecule ◽  
Single Cell Analysis ◽  
Cell Model ◽  
Single Cells ◽  
Single Gene ◽  
Gene Activation ◽  
Light Activation ◽  
Dynamic Synthesis ◽  
Single Cell Model

Single-cell analysis has revealed that transcription is dynamic and stochastic, but tools are lacking that can determine the mechanism operating at a single gene. Here we utilize single-molecule observations of RNA in fixed and living cells to develop a single-cell model of steroid-receptor mediated gene activation. We determine that steroids drive mRNA synthesis by frequency modulation of transcription. This digital behavior in single cells gives rise to the well-known analog dose response across the population. To test this model, we developed a light-activation technology to turn on a single steroid-responsive gene and follow dynamic synthesis of RNA from the activated locus.

scholarly journals Prokaryotic Single-Cell RNA Sequencing by In Situ Combinatorial Indexing

2019 ◽  
Author(s):  
Sydney B. Blattman ◽  
Wenyan Jiang ◽  
Panos Oikonomou ◽  
Saeed Tavazoie
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Low Cost ◽  
Bacterial Cells ◽  
Single Experiment ◽  
Bacterial Populations ◽  
Single Cell Rna Sequencing ◽  
Gene Expression Heterogeneity ◽  
Mrna Polyadenylation

AbstractDespite longstanding appreciation of gene expression heterogeneity in isogenic bacterial populations, affordable and scalable technologies for studying single bacterial cells have been limited. While single-cell RNA sequencing (scRNA-seq) has revolutionized studies of transcriptional heterogeneity in diverse eukaryotic systems, application of scRNA-seq to prokaryotes has been hindered by their extremely low mRNA abundance, lack of mRNA polyadenylation, and thick cell walls. Here, we present Prokaryotic Expression-profiling by Tagging RNA In Situ and sequencing (PETRI-seq), a low-cost, high-throughput, prokaryotic scRNA-seq pipeline that overcomes these technical obstacles. PETRI-seq uses in situ combinatorial indexing to barcode transcripts from tens of thousands of cells in a single experiment. PETRI-seq captures single cell transcriptomes of Gram-negative and Gram-positive bacteria with high purity and low bias, with median capture rates >200 mRNAs/cell for exponentially growing E. coli. These characteristics enable robust discrimination of cell-states corresponding to different phases of growth. When applied to wild-type S. aureus, PETRI-seq revealed a rare sub-population of cells undergoing prophage induction. We anticipate broad utility of PETRI-seq in defining single-cell states and their dynamics in complex microbial communities.

scholarly journals High resolution AKT signaling in individual cells

2018 ◽  
Author(s):  
Sean M. Gross ◽  
Mark A. Dane ◽  
Elmar Bucher ◽  
Laura M. Heiser
Keyword(s):  
Single Cell ◽  
Intracellular Signaling ◽  
Time Course ◽  
Dynamic Range ◽  
Individual Cell ◽  
Akt Signaling ◽  
Live Cells ◽  
Theoretic Approach ◽  
Wide Range ◽  
Igf I

AbstractCells sense and respond to their environment by activating distinct intracellular signaling pathways, however an individual cell’s ability to faithfully transmit and discriminate environmental signals is thought to be limited. To assess the fidelity of signal transmission in the PI3K-AKT signaling pathway, we first developed an optimized genetically encoded sensor that had an increased dynamic range and reduced variation under basal conditions. We then used this reporter to track responses to varying doses of IGF-I in live cells and found that signaling responses from individual cells overlapped across a wide range of IGF-I doses, suggesting limited transmission accuracy. However, further analysis of individual cell traces revealed that responses were constant over time without stochastic fluctuations. We devised a new information theoretic approach to calculate the channel capacity using variance of the single cell time course data‐‐rather than population-level variance as has been previously used—and predicted that cells were capable of discriminating multiple growth factor doses. We validated these predictions by tracking individual cell responses to multiple IGF-I doses and found that cells can accurately distinguish at least four different IGF-I concentrations, as demonstrated by their distinct responses. Furthermore, we found a similar discriminatory ability to pathway inhibition, as assessed by responses to the PI3K inhibitor alpelisib. Our studies indicate that cells can faithfully transmit an IGF-I input into a down-stream signaling response and that heterogeneous responses result from variation in the input-output relation across the population. These observations reveal the importance of viewing each cell as having its own communication channel and underscore the importance of understanding responses at the single cell level.

Stacking Cell Model Supercapacitor Asymmetry with Multilayer Reduced Graphene Oxide Films Fabricated Using UV Oven Spraying Technique

2021 ◽  
Vol 1028 ◽  
pp. 127-132
Author(s):  
Norman Syakir ◽  
Diyan Unmu Dzujah ◽  
Rahmat Hidayat ◽  
Fitrilawati
Keyword(s):  
Graphene Oxide ◽  
Energy Density ◽  
Single Cell ◽  
Reduced Graphene Oxide ◽  
Power Density ◽  
Cell Model ◽  
Oxide Films ◽  
Capacitance Density ◽  
Reduced Graphene ◽  
Power And Energy

We report the fabrication of multilayer reduced graphene oxide films using UV oven spraying technique for stacking cell model supercapacitor asymmetry. In report, we used nickel and carbon substrates as asymmetric current collectors. Using UV oven spraying technique, graphene oxide was coated and insitu converted on substrate surfaces forming reduced graphene oxide films that act as active materials in supercapacitor asymmetry. The films consist of 70 layers with delay time between consecutive layer prior to irradiation is 4 minutes to ensure the photoreduction take place on each layer. UV light source using Mercury lamp 125 watt at 30 cm above the substrates. The model structures consist of three cells stacked serial in 1M KCl electrolyte system. Device performance was characterized using charge-discharge technique for constant current at 2, 3, 4, 5, and 10 mA. Performance parameters are the capacitance density, power and energy density. Single cell supercapacitor has energy density in range of 0.072 Wh/kg to 0.256 Wh/kg and power density in range of 123.06 W/kg to 644.14 W/kg. Meanwhile for stacked cell supercapacitor has energy density in range of 0.377 Wh/kg to 0.755 Wh/kg, and power density in range of 169.95 W/kg to 849.79 W/kg. According to Ragone Plot, the results have feature as supercapacitor, even as single cell. Stacked cell has feature better than single cell in all parameter of capacitance density, power and energy density, and electrical working potential.

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