scholarly journals Arrhythmia Mechanisms and Spontaneous Calcium Release: I - Multi-scale Modelling Approaches

2018 ◽  
Author(s):  
Michael A. Colman
Keyword(s):  
Single Cell ◽  
Calcium Release ◽  
Cell Model ◽  
Single Cells ◽  
Computational Modelling ◽  
Calcium Handling ◽  
Spontaneous Release ◽  
Multi Scale ◽  
Cellular Models ◽  
Tissue Models

AbstractMotivationSpontaneous sub-cellular calcium release events (SCRE), controlled by microscopic stochastic fluctuations of the proteins responsible for intracellular calcium release, are conjectured to promote the initiation and perpetuation of rapid arrhythmia associated with conditions such as heart failure and atrial fibrillation: SCRE may underlie the emergence of spontaneous excitation in single cells, resulting in arrhythmic triggers in tissue. However, translation of single-cell data to the tissue scale is non-trivial due to complex substrate considerations. Computational modelling provides a viable approach to dissect these multi-scale mechanisms, yet there remains a significant challenge in accurately and efficiently modelling this probabilistic behaviour in large-scale tissue models. The aim of this study was to develop an approach to overcome this challenge.MethodsThe dynamics of SCRE under multiple conditions (pacing rate, beta-stimulation, disease remodelling) in a computational model of stochastic, spatio-temporal calcium handling were analysed in order to develop Spontaneous Release Functions, which capture the variability and properties of SCRE matched to the full cell model. These functions were then integrated with tissue models, comprising idealised 2D sheets as well as full reconstructions of ventricular and atrial anatomy.ResultsThe Spontaneous Release Functions accurately reproduced the dynamics of SCRE and its dependence on environment variables under multiple different conditions observed in the full single-cell model. Differences between cellular models and conditions where enhanced at the tissue scale, where the emergence of a focal excitation is largely an all-or-nothing response. Generalisation of the approaches was demonstrated through integration with an independent cell model, and parameterisation to an experimental dataset.ConclusionsA novel approach has been developed to dynamically model SCRE at the tissue scale, in-line with behaviour observed in detailed single-cell models. Such an approach allows evaluation of the potential importance of SCRE in arrhythmia in both general mechanistic and disease-specific investigation.

scholarly journals Spontaneous calcium release in tissue from the failing canine heart

2009 ◽  
Vol 297 (4) ◽  
pp. H1235-H1242 ◽  
Author(s):  
Gregory S. Hoeker ◽  
Rodolphe P. Katra ◽  
Lance D. Wilson ◽  
Bradley N. Plummer ◽  
Kenneth R. Laurita
Keyword(s):  
Sarcoplasmic Reticulum ◽  
Calcium Release ◽  
Tissue Level ◽  
Calcium Handling ◽  
Canine Heart ◽  
Myocardial Cells ◽  
Spontaneous Release ◽  
Adrenergic Stimulation ◽  
Electrical Instability ◽  
Delayed Afterdepolarization

Abnormalities in calcium handling have been implicated as a significant source of electrical instability in heart failure (HF). While these abnormalities have been investigated extensively in isolated myocytes, how they manifest at the tissue level and trigger arrhythmias is not clear. We hypothesize that in HF, triggered activity (TA) is due to spontaneous calcium release from the sarcoplasmic reticulum that occurs in an aggregate of myocardial cells (an SRC) and that peak SCR amplitude is what determines whether TA will occur. Calcium and voltage optical mapping was performed in ventricular wedge preparations from canines with and without tachycardia-induced HF. In HF, steady-state calcium transients have reduced amplitude [135 vs. 170 ratiometric units (RU), P < 0.05] and increased duration (252 vs. 229 s, P < 0.05) compared with those of normal. Under control conditions and during β-adrenergic stimulation, TA was more frequent in HF (53% and 93%, respectively) compared with normal (0% and 55%, respectively, P < 0.025). The mechanism of arrhythmias was SCRs, leading to delayed afterdepolarization-mediated triggered beats. Interestingly, the rate of SCR rise was greater for events that triggered a beat (0.41 RU/ms) compared with those that did not (0.18 RU/ms, P < 0.001). In contrast, there was no difference in SCR amplitude between the two groups. In conclusion, TA in HF tissue is associated with abnormal calcium regulation and mediated by the spontaneous release of calcium from the sarcoplasmic reticulum in aggregates of myocardial cells (i.e., an SCR), but importantly, it is the rate of SCR rise rather than amplitude that was associated with TA.

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 Performance Comparison of Reverse Transcriptases for Single-Cell Studies

2019 ◽  
Vol 66 (1) ◽  
pp. 217-228 ◽  
Author(s):  
Daniel Zucha ◽  
Peter Androvic ◽  
Mikael Kubista ◽  
Lukas Valihrach
Keyword(s):  
Single Cell ◽  
Reverse Transcription ◽  
Cell Model ◽  
Single Cells ◽  
Performance Comparison ◽  
Reaction Yield ◽  
Reverse Transcriptases ◽  
Reverse Transcription Pcr ◽  
Cell Experiment ◽  
Almost All

Abstract BACKGROUND Recent advances allowing quantification of RNA from single cells are revolutionizing biology and medicine. Currently, almost all single-cell transcriptomic protocols rely on reverse transcription (RT). However, RT is recognized as a known source of variability, particularly with low amounts of RNA. Recently, several new reverse transcriptases (RTases) with the potential to decrease the loss of information have been developed, but knowledge of their performance is limited. METHODS We compared the performance of 11 RTases in quantitative reverse transcription PCR (RT-qPCR) on single-cell and 100-cell bulk templates, using 2 priming strategies: a conventional mixture of random hexamers with oligo(dT)s and a reduced concentration of oligo(dT)s mimicking common single-cell RNA-sequencing protocols. Depending on their performance, 2 RTases were further tested in a high-throughput single-cell experiment. RESULTS All tested RTases demonstrated high precision (R2 &gt; 0.9445). The most pronounced differences were found in their ability to capture rare transcripts (0%–90% reaction positivity rate) and in their absolute reaction yield (7.3%–137.9%). RTase performance and reproducibility were compared with Z scores. The 2 best-performing enzymes were Maxima H− and SuperScript IV. The validity of the obtained results was confirmed in a follow-up single-cell model experiment. The better-performing enzyme (Maxima H−) increased the sensitivity of the single-cell experiment and improved resolution in the clustering analysis over the commonly used RTase (SuperScript II). CONCLUSIONS Our comprehensive comparison of 11 RTases in low RNA input conditions identified 2 best-performing enzymes. Our results provide a point of reference for the improvement of current single-cell quantification protocols.

scholarly journals Arrhythmia Mechanisms and Spontaneous Calcium Release: II - From Calcium Spark to Re-entry and Back

2018 ◽  
Author(s):  
Michael A. Colman
Keyword(s):  
Calcium Release ◽  
Single Cells ◽  
Computational Cost ◽  
Conduction Block ◽  
Spiral Wave ◽  
Positive Role ◽  
Pharmacological Management ◽  
Calcium Dependent ◽  
Tissue Models

AbstractMotivationThe role of sub-cellular spontaneous calcium release events (SCRE) in the development of arrhythmia associated with atrial and ventricular tachycardia and fibrillation has yet to be investigated in detail. SCRE may underlie the emergence of spontaneous excitation in single cells, resulting in arrhythmic triggers in tissue. Furthermore, they can promote the substrate for conduction abnormalities. However, the potential interactions with re-entrant excitation have yet to be explored. The primary aim of this study was therefore to apply a novel computational approach to understand the multi-scale coupling between re-entrant excitation and SCRE.MethodsA general implementation of Spontaneous Release Functions - which reproduce the calcium dependent SCRE dynamics of detailed cell models at a significantly reduced computational cost - was used to reproduce SCRE in tissue models. Arrhythmic dynamics, such as rapid pacing and re-entry, were induced in the tissue models and the resulting interactions with SCRE were analysed.ResultsIn homogeneous tissue, the emergence of a spontaneous beat from a single source was observed and the positive role of coupling was demonstrated. Conduction block could be promoted by SCRE by both inactivation of the fast sodium channel as well as focal pacing heterogeneity interactions. Sustained re-entrant excitation promoted calcium overload, and led to the emergence of focal excitations both after termination of re-entry and also during re-entrant excitation. These results demonstrated a purely functional mechanism of re-entry and focal activity localisation, related to the unexcited spiral wave core.ConclusionsSCRE may interact with tissue excitation to promote and perpetuate arrhythmia through multiple mechanisms, including functional localisation and mechanism switching. These insights may be particularly relevant for successful pharmacological management of arrhythmia.

scholarly journals Performance comparison of reverse transcriptases for single-cell studies

2019 ◽  
Author(s):  
Zucha Daniel ◽  
Androvic Peter ◽  
Kubista Mikael ◽  
Valihrach Lukas
Keyword(s):  
Single Cell ◽  
Cell Model ◽  
Single Cells ◽  
Performance Comparison ◽  
Reverse Transcriptases ◽  
Single Cell Model ◽  
Cell Experiment ◽  
Z Scores ◽  
Technical Advances ◽  
Almost All

ABSTRACTBackgroundRecent technical advances allowing quantification of RNA from single cells are revolutionizing biology and medicine. Currently, almost all single-cell transcriptomic protocols rely on conversion of RNA to cDNA by reverse transcription (RT). However, RT is recognized as highly limiting step due to its inherent variability and suboptimal sensitivity, especially at minute amounts of RNA. Primary factor influencing RT outcome is reverse transcriptase (RTase). Recently, several new RTases with potential to decrease the loss of information during RT have been developed, but the thorough assessment of their performance is missing.MethodsWe have compared the performance of 11 RTases in RT-qPCR on single-cell and 100-cell bulk templates using two priming strategies: conventional mixture of random hexamers with oligo(dT)s and reduced concentration of oligo(dT)s mimicking common single-cell RNA-Seq library preparation protocols. Based on the performance, two RTases were further tested in high-throughput single-cell experiment.ResultsAll RTases tested reverse transcribed low-concentration templates with high accuracy (R2 > 0.9445) but variable reproducibility (median CVRT = 40.1 %). The most pronounced differences were found in the ability to capture rare transcripts (0 - 90% reaction positivity rate) as well as in the rate of RNA conversion to cDNA (7.3 - 124.5 % absolute yield). Finally, RTase performance and reproducibility across all tested parameters were compared using Z-scores and validity of obtained results was confirmed in a single-cell model experiment. The better performing RTase provided higher positive reaction rate and expression levels and improved resolution in clustering analysis.ConclusionsWe performed a comprehensive comparison of 11 RTases in low RNA concentration range and identified two best-performing enzymes (Maxima H-; SuperScript IV). We found that using better-performing enzyme (Maxima H-) over commonly-used below-average performer (SuperScript II) increases the sensitivity of single-cell experiment. Our results provide a reference for the improvement of current single-cell quantification protocols.

Single-cell analyses of nitrergic neurons in simple nervous systems

1999 ◽  
Vol 202 (4) ◽  
pp. 333-341 ◽  
Author(s):  
L.L. Moroz ◽  
R. Gillette ◽  
J.V. Sweedler
Keyword(s):  
Single Cell ◽  
Cell Model ◽  
Single Cells ◽  
Chemical Species ◽  
No Oxidation ◽  
Cell Level ◽  
Pharmacological Manipulations ◽  
Physiological And Biochemical

Understanding the role of the gaseous messenger nitric oxide (NO) in the nervous system is complicated by the heterogeneity of its nerve cells; analyses carried out at the single cell level are therefore important, if not critical. Some invertebrate preparations, most especially those from the gastropod molluscs, provide large, hardy and identified neurons that are useful both for the development of analytical methodologies and for cellular analyses of NO metabolism and its actions. Recent modifications of capillary electrophoresis (CE) allow the use of a small fraction of an individual neuron to perform direct, quantitative and simultaneous assays of the major metabolites of the NO-citrulline cycle and associated biochemical pathways. These chemical species include the products of NO oxidation (NO2-/NO3-), l-arginine, l-citrulline, l-ornithine, l-argininosuccinate, as well as selected NO synthase inhibitors and cofactors such as NADPH, biopterin, FMN and FAD. Diverse cotransmitters can also be identified in the same nitrergic neuron. The sensitivity of CE methods is in the femtomole to attomole range, depending on the species analysed and on the specific detector used. CE analysis can be combined with prior in vivo electrophysiological and pharmacological manipulations and measurements to yield multiple physiological and biochemical values from single cells. The methodologies and instrumentation developed and tested using the convenient molluscan cell model can be adapted to the smaller and more delicate neurons of other invertebrates and chordates.

scholarly journals A Patient-based Model to Investigate the Effect of Micro-structure Scars on the Optogenetic Defibrillation Success: A Computational Modelling Approach

2020 ◽  
Author(s):  
Elham Zakeri Zafarghandi ◽  
Fariba Bahrami
Keyword(s):  
Single Cell ◽  
Cardiac Tissue ◽  
Cell Model ◽  
Success Probability ◽  
Computational Cost ◽  
Computational Modelling ◽  
Relative Area ◽  
Imaging Data ◽  
Data Set ◽  
Interface Length

AbstractThis study investigates the role of the microstructure of real scars in the success of optogenetic defibrillation. To reduce the computational cost of high-order models (like Ten Tusscher Model, TTM) for a single cell as well as to take advantage of their ability to generate a more realistic output, we developed a low-order model of optogenetic cardiac tissue based on the modified Alieve-Panfilov single-cell model and estimated its parameters using a TTM. Two-dimensional electrophysiological cardiac tissue models were produced including different scar shapes that were extracted from Late Gadolinium-Enhanced (LGE) magnetic resonance imaging data set of 10 patients with non-ischemic dilated cardiomyopathy. The scar shapes were classified based on four criteria: transmurality, relative area, scar entropy, and interface length. Scar with the highest 25% of the relative area showed 25% of successful cases, this ratio is 27%, and 25% for a scar with the most top 25% of entropy, and transmurality, respectively. In comparison, the proportions are 61.54%, 44.44%, and 61.76%, for the lowest 25% of the area, entropy, and transmurality. We also investigated the efficacy of various methods for light-sensitive cells’ distribution within the cardiac tissue with scar. Four types of distributions were defined. Defibrillation within tissues with 0.1 light-sensitive out of all cells was 15 to 25% more successful than their counterparts with 0.05 light-sensitive cells. Lastly, we examined the effect of an earlier stimulation on the success probability of defibrillation. Our results indicated that inducing 0.5 msec earlier resulted in a roughly 15% rise in successful cases.

scholarly journals Simulating single-cell metabolism using a stochastic flux-balance analysis algorithm

2020 ◽  
Author(s):  
David S. Tourigny ◽  
Arthur P. Goldberg ◽  
Jonathan R. Karr
Keyword(s):  
Single Cell ◽  
Stochastic Simulation ◽  
Flux Balance Analysis ◽  
Cell Biology ◽  
Stochastic Dynamics ◽  
Cell Model ◽  
Single Cells ◽  
Computational Techniques ◽  
Flux Balance ◽  
Balance Analysis

AbstractStochasticity from gene expression in single cells is known to drive metabolic heterogeneity at the population-level, which is understood to have important consequences for issues such as microbial drug tolerance and treatment of human diseases like cancer. Experimental methods for probing metabolism in single cells currently lag far behind advancements in single-cell genomics, transcriptomics, and proteomics, which motivates the development of computational techniques to bridge this gap in the systems approach to single-cell biology. In this paper, we present SSA-FBA (stochastic simulation algorithm with flux-balance analysis embedded) as a modelling framework for simulating the stochastic dynamics of metabolism in individual cells. SSA-FBA extends the constraint-based formalism of metabolic network modelling to the single-cell regime, providing a suitable approach to simulation when kinetic information is lacking from models. We also describe an advanced algorithm that significantly improves the efficiency of exact SSA-FBA simulations, which is necessary because of the computational costs associated with stochastic simulation and the observation that approximations can be inaccurate and numerically unstable. As a preliminary case study we apply SSA-FBA to a single-cell model of Mycoplasma pneumoniae, and explore the use of simulation to understand the role of stochasticity in metabolism at the single-cell level.

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.

In-Situ Dual Beam (FIBSEM) Techniques for Probe Pad Deposition and Dielectric Integrity Inspection in 0.2 μm Technology DRAM Single Cells

1999 ◽  
Author(s):  
Gunnar Zimmermann ◽  
Richard Chapman
Keyword(s):  
Electron Beam ◽  
Single Cell ◽  
Single Cells ◽  
Ion Beam ◽  
Gate Oxide ◽  
Ion Milling ◽  
Dual Beam ◽  
Sem Imaging ◽  
Innovative Techniques

Abstract Dual beam FIBSEM systems invite the use of innovative techniques to localize IC fails both electrically and physically. For electrical localization, we present a quick and reliable in-situ FIBSEM technique to deposit probe pads with very low parasitic leakage (Ipara &lt; 4E-11A at 3V). The probe pads were Pt, deposited with ion beam assistance, on top of highly insulating SiOx, deposited with electron beam assistance. The buried plate (n-Band), p-well, wordline and bitline of a failing and a good 0.2 μm technology DRAM single cell were contacted. Both cells shared the same wordline for direct comparison of cell characteristics. Through this technique we electrically isolated the fail to a single cell by detecting leakage between the polysilicon wordline gate and the cell diffusion. For physical localization, we present a completely in-situ FIBSEM technique that combines ion milling, XeF2 staining and SEM imaging. With this technique, the electrically isolated fail was found to be a hole in the gate oxide at the bad cell.

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