scholarly journals Assessing the Impact of Single-Cell Stimulation on Local Networks in Rat Barrel Cortex—A Feasibility Study

2019 ◽  
Vol 20 (10) ◽  
pp. 2604
Author(s):  
Beate Knauer ◽  
Maik C. Stüttgen
Keyword(s):  
Single Cell ◽  
Statistical Power ◽  
Single Cells ◽  
Network Activity ◽  
Local Network ◽  
Brain State ◽  
Population Activity ◽  
Local Networks ◽  
Cell Stimulation ◽  
The Impact

In contrast to the long-standing notion that the role of individual neurons in population activity is vanishingly small, recent studies have shown that electrical activation of only a single cortical neuron can have measurable effects on global brain state, movement, and perception. Although highly important for understanding how neuronal activity in cortex is orchestrated, the cellular and network mechanisms underlying this phenomenon are unresolved. Here, we first briefly review the current state of knowledge regarding the phenomenon of single-cell induced network modulation and discuss possible underpinnings. Secondly, we show proof of principle for an experimental approach to elucidate the mechanisms of single-cell induced changes in cortical activity. The setup allows simultaneous recordings of the spiking activity of multiple neurons across all layers of the cortex using a multi-electrode array, while manipulating the activity of one individual neuron in close proximity to the array. We demonstrate that single cells can be recorded and stimulated reliably for hundreds of trials, conferring high statistical power even for expectedly small effects of single-neuron spiking on network activity. Preliminary results suggest that single-cell stimulation on average decreases the firing rate of local network units. We expect that characterization of the spatiotemporal spread of single-cell evoked activity across layers and columns will yield novel insights into intracortical processing.

scholarly journals Imaging of respiratory-related population activity with single-cell resolution

2007 ◽  
Vol 292 (1) ◽  
pp. C508-C516 ◽  
Author(s):  
Frank Funke ◽  
Mathias Dutschmann ◽  
Michael Müller
Keyword(s):  
Single Cell ◽  
Neuronal Activity ◽  
Single Cells ◽  
Activity Patterns ◽  
Respiratory Rhythm ◽  
Network Activity ◽  
Respiratory Neurons ◽  
Ventrolateral Medulla ◽  
Population Activity ◽  
Respiratory Network

The pre-Bötzinger complex (PBC) in the rostral ventrolateral medulla contains a kernel involved in respiratory rhythm generation. So far, its respiratory activity has been analyzed predominantly by electrophysiological approaches. Recent advances in fluorescence imaging now allow for the visualization of neuronal population activity in rhythmogenic networks. In the respiratory network, voltage-sensitive dyes have been used mainly, so far, but their low sensitivity prevents an analysis of activity patterns of single neurons during rhythmogenesis. We now have succeeded in using more sensitive Ca2+ imaging to study respiratory neurons in rhythmically active brain stem slices of neonatal rats. For the visualization of neuronal activity, fluo-3 was suited best in terms of neuronal specificity, minimized background fluorescence, and response magnitude. The tissue penetration of fluo-3 was improved by hyperosmolar treatment (100 mM mannitol) during dye loading. Rhythmic population activity was imaged with single-cell resolution using a sensitive charge-coupled device camera and a ×20 objective, and it was correlated with extracellularly recorded mass activity of the contralateral PBC. Correlated optical neuronal activity was obvious online in 29% of slices. Rhythmic neurons located deeper became detectable during offline image processing. Based on their activity patterns, 74% of rhythmic neurons were classified as inspiratory and 26% as expiratory neurons. Our approach is well suited to visualize and correlate the activity of several single cells with respiratory network activity. We demonstrate that neuronal synchronization and possibly even network configurations can be analyzed in a noninvasive approach with single-cell resolution and at frame rates currently not reached by most scanning-based imaging techniques.

scholarly journals The effect of single pyramidal neuron firing across and within layers in mouse V1

2017 ◽  
Author(s):  
Jochen Meyer ◽  
Peyman Golshani ◽  
Stelios M. Smirnakis
Keyword(s):  
Patch Clamp ◽  
Single Cell ◽  
Pyramidal Cell ◽  
Pyramidal Neurons ◽  
Population Activity ◽  
Cell Stimulation ◽  
Layer 2 ◽  
Layer 4 ◽  
Aggregate Population ◽  
The Impact

AbstractThe influence of cortical cell spiking activity on nearby cells has been studied extensively in vitro. Less is known, however, about the impact of single cell firing on local cortical networks in vivo. In a pioneering study, Kwan et al. (Kwan et al., 2012) reported that in mouse layer 2/3 (L2/3), under anesthesia, stimulating a single pyramidal cell recruits ~1.7% of neighboring pyramidal units. Here we employ two-photon calcium imaging, in conjunction with single-cell patch clamp stimulation, to probe, in both the awake and lightly anesthetized states, how i) activating single L2/3 pyramidal neurons recruits neighboring units within L2/3 and from layer 4 (L4) to L2/3, and whether ii) activating single pyramidal neurons changes population activity in local circuit. To do this, it was essential to develop an algorithm capable of quantifying how sensitive the calcium signal is at detecting effectively recruited units (“followers”). This algorithm allowed us to estimate the chance of detecting a follower as a function of the probability that an epoch of stimulation elicits one extra action potential (AP) in the follower cell. Using this approach, we found only a small fraction (<0.75%) of L2/3 cells to be significantly activated within a radius of ~200 μm from a stimulated neighboring L2/3 pyramidal cell. This fraction did not change significantly in the awake versus the lightly anesthetized state, nor when stimulating L2/3 versus underlying L4 pyramidal neurons. These numbers are in general agreement with, though lower than, the percentage of neighboring cells (2.1%) reported by Kwan et al. to be activated upon stimulating single L2/3 pyramidal neurons under anesthesia (Kwan et al., 2012). Interestingly, despite the small number of individual units found to be reliably driven, we did observe a modest but significant elevation in aggregate population responses compared to sham stimulation. This underscores the distributed impact that single cell stimulation has on neighboring microcircuit responses, revealing only a small minority of relatively strongly connected partners.One Sentence SummaryPatch-clamp stimulation in conjunction with 2-photon imaging shows that activating single layer-2/3 or layer-4 pyramidal neurons produces few (<1% of local units) reliable singlecell followers in L2/3 of mouse area V1, either under light anesthesia or in quiet wakefulness: instead, single cell stimulation was found to elevate aggregate population activity in a weak but highly distributed fashion.

scholarly journals Morphodynamic signatures of MDA-MB-231 single cells and cell doublets undergoing invasion in confined microenvironments

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xingjian Zhang ◽  
Trevor Chan ◽  
Michael Mak
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Leading Edge ◽  
Cell Group ◽  
Collective State ◽  
Long Term Effects ◽  
Cell Metastasis ◽  
Geometric Confinement ◽  
Short And Long Term ◽  
The Impact

AbstractCancer cell metastasis is a major factor in cancer-related mortality. During the process of metastasis, cancer cells exhibit migratory phenotypes and invade through pores in the dense extracellular matrix. However, the characterization of morphological and subcellular features of cells in similar migratory phenotypes and the effects of geometric confinement on cell morphodynamics are not well understood. Here, we investigate the phenotypes of highly aggressive MDA-MB-231 cells in single cell and cell doublet (an initial and simplified collective state) forms in confined microenvironments. We group phenotypically similar single cells and cell doublets and characterize related morphological and subcellular features. We further detect two distinct migratory phenotypes, fluctuating and non-fluctuating, within the fast migrating single cell group. In addition, we demonstrate an increase in the number of protrusions formed at the leading edge of cells after invasion through geometric confinement. Finally, we track the short and long term effects of varied degrees of confinement on protrusion formation. Overall, our findings elucidate the underlying morphological and subcellular features associated with different single cell and cell doublet phenotypes and the impact of invasion through confined geometry on cell behavior.

scholarly journals Quality assessment of single-cell RNA sequencing data by coverage skewness analysis

2019 ◽  
Author(s):  
Imad Abugessaisa ◽  
Shuhei Noguchi ◽  
Melissa Cardon ◽  
Akira Hasegawa ◽  
Kazuhide Watanabe ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cells ◽  
Assessment Method ◽  
Poor Quality ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Gene Coverage ◽  
The Impact

AbstractAnalysis and interpretation of single-cell RNA-sequencing (scRNA-seq) experiments are compromised by the presence of poor quality cells. For meaningful analyses, such poor quality cells should be excluded to avoid biases and large variation. However, no clear guidelines exist. We introduce SkewC, a novel quality-assessment method to identify poor quality single-cells in scRNA-seq experiments. The method is based on the assessment of gene coverage for each single cell and its skewness as a quality measure. To validate the method, we investigated the impact of poor quality cells on downstream analyses and compared biological differences between typical and poor quality cells. Moreover, we measured the ratio of intergenic expression, suggesting genomic contamination, and foreign organism contamination of single-cell samples. SkewC is tested in 37,993 single-cells generated by 15 scRNA-seq protocols. We envision SkewC as an indispensable QC method to be incorporated into scRNA-seq experiment to preclude the possibility of scRNA-seq data misinterpretation.

Testing of solid oxide cells at high current densities

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
André Weber
Keyword(s):  
Single Cell ◽  
High Performance ◽  
High Efficiency ◽  
Electrochemical Impedance ◽  
Single Cells ◽  
Operating Conditions ◽  
Solid Oxide ◽  
Current Densities ◽  
Cell Testing ◽  
The Impact

Abstract Solid Oxide Cells (SOCs) have gained an increasing interest as electrochemical energy converters due to their high efficiency, fuel flexibility and ability of reversible fuel cell/electrolysis operation. During the development process as well as in quality assurance tests, the performance of single cells and cell stacks is commonly evaluated by means of current/voltage- (CV-) characteristics. Despite of the fact that the measurement of a CV-characteristic seems to be simple compared to more complex, dynamic methods as electrochemical impedance spectroscopy or current interrupt techniques, the resulting performance strongly depends on the test setup and the chosen operating conditions. In this paper, the impact of different single cell testing environments and operating conditions on the CV-characteristic of high performance cells is discussed. The influence of cell size, contacting and current collection, contact pressure, fuel flow rate and composition on the achievable cell performance is presented and limitations arising from the test bed and testing conditions will be pointed out. As today’s high performance cells are capable of delivering current densities of several ampere per cm2 a special emphasis will be laid on single cell testing in this current range.

scholarly journals Dissecting heterogeneous cell populations across drug and disease conditions with PopAlign

2020 ◽  
Vol 117 (46) ◽  
pp. 28784-28794
Author(s):  
Sisi Chen ◽  
Paul Rivaud ◽  
Jong H. Park ◽  
Tiffany Tsou ◽  
Emeric Charles ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Large Scale ◽  
Probabilistic Models ◽  
Single Cells ◽  
Measurement Techniques ◽  
Patient Specific ◽  
Cell Populations ◽  
Cell Measurement ◽  
The Impact

Single-cell measurement techniques can now probe gene expression in heterogeneous cell populations from the human body across a range of environmental and physiological conditions. However, new mathematical and computational methods are required to represent and analyze gene-expression changes that occur in complex mixtures of single cells as they respond to signals, drugs, or disease states. Here, we introduce a mathematical modeling platform, PopAlign, that automatically identifies subpopulations of cells within a heterogeneous mixture and tracks gene-expression and cell-abundance changes across subpopulations by constructing and comparing probabilistic models. Probabilistic models provide a low-error, compressed representation of single-cell data that enables efficient large-scale computations. We apply PopAlign to analyze the impact of 40 different immunomodulatory compounds on a heterogeneous population of donor-derived human immune cells as well as patient-specific disease signatures in multiple myeloma. PopAlign scales to comparisons involving tens to hundreds of samples, enabling large-scale studies of natural and engineered cell populations as they respond to drugs, signals, or physiological change.

scholarly journals Computation of Single-Cell Metabolite Distributions Using Mixture Models

2020 ◽  
Vol 8 ◽  
Author(s):  
Mona K. Tonn ◽  
Philipp Thomas ◽  
Mauricio Barahona ◽  
Diego A. Oyarzún
Keyword(s):  
Single Cell ◽  
Mixture Models ◽  
Single Cells ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Stochastic Simulations ◽  
Deterministic Models ◽  
Metabolic Heterogeneity ◽  
Cell Expression ◽  
The Impact

Metabolic heterogeneity is widely recognized as the next challenge in our understanding of non-genetic variation. A growing body of evidence suggests that metabolic heterogeneity may result from the inherent stochasticity of intracellular events. However, metabolism has been traditionally viewed as a purely deterministic process, on the basis that highly abundant metabolites tend to filter out stochastic phenomena. Here we bridge this gap with a general method for prediction of metabolite distributions across single cells. By exploiting the separation of time scales between enzyme expression and enzyme kinetics, our method produces estimates for metabolite distributions without the lengthy stochastic simulations that would be typically required for large metabolic models. The metabolite distributions take the form of Gaussian mixture models that are directly computable from single-cell expression data and standard deterministic models for metabolic pathways. The proposed mixture models provide a systematic method to predict the impact of biochemical parameters on metabolite distributions. Our method lays the groundwork for identifying the molecular processes that shape metabolic heterogeneity and its functional implications in disease.

scholarly journals Single-cell analysis of HIV-1 transcriptional activity reveals expression of proviruses in expanded clones during ART

2017 ◽  
Vol 114 (18) ◽  
pp. E3659-E3668 ◽  
Author(s):  
Ann Wiegand ◽  
Jonathan Spindler ◽  
Feiyu F. Hong ◽  
Wei Shao ◽  
Joshua C. Cyktor ◽  
...  
Keyword(s):  
Single Cell ◽  
Mononuclear Cells ◽  
Single Cells ◽  
Constitutive Expression ◽  
Multiple Time ◽  
Hiv Rna ◽  
Infected Cells ◽  
The Impact ◽  
Hiv 1

Little is known about the fraction of human immunodeficiency virus type 1 (HIV-1) proviruses that express unspliced viral RNA in vivo or about the levels of HIV RNA expression within single infected cells. We developed a sensitive cell-associated HIV RNA and DNA single-genome sequencing (CARD-SGS) method to investigate fractional proviral expression of HIV RNA (1.3-kb fragment of p6, protease, and reverse transcriptase) and the levels of HIV RNA in single HIV-infected cells from blood samples obtained from individuals with viremia or individuals on long-term suppressive antiretroviral therapy (ART). Spiking experiments show that the CARD-SGS method can detect a single cell expressing HIV RNA. Applying CARD-SGS to blood mononuclear cells in six samples from four HIV-infected donors (one with viremia and not on ART and three with viremia suppressed on ART) revealed that an average of 7% of proviruses (range: 2–18%) expressed HIV RNA. Levels of expression varied from one to 62 HIV RNA molecules per cell (median of 1). CARD-SGS also revealed the frequent expression of identical HIV RNA sequences across multiple single cells and across multiple time points in donors on suppressive ART consistent with constitutive expression of HIV RNA in infected cell clones. Defective proviruses were found to express HIV RNA at levels similar to those proviruses that had no obvious defects. CARD-SGS is a useful tool to characterize fractional proviral expression in single infected cells that persist despite ART and to assess the impact of experimental interventions on proviral populations and their expression.

Reaction Time and Time Course of Neuronal Responses in MT and MST at Different Stimulus Contrasts

Perception ◽  
1996 ◽  
Vol 25 (1_suppl) ◽  
pp. 157-157 ◽  
Author(s):  
A Thiele ◽  
K-P Hoffmann
Keyword(s):  
Reaction Time ◽  
Single Cell ◽  
Single Cells ◽  
Direction Selectivity ◽  
Contrast Level ◽  
Population Activity ◽  
Temporal Area ◽  
Population Mean ◽  
The Mean ◽  
Mean Reaction Time

Direction-selective neurons from the middle temporal area (MT) and the middle superior temporal area (MST) were recorded while a monkey performed a direction discrimination task. Stimuli consisted of evenly spaced bars moving in one of the four cardinal directions. Monkey's reaction time, single-cell latency, and direction selectivity were calculated when stimuli of 53%, 24%, and 4% contrast were presented, and the monkey indicated a correct decision. Mean reaction time was 359±77 ms at 53% contrast, 391±107 ms at 24% contrast, and 582±374 ms at 4% contrast. Most neurons exhibiting direction selective responses at 53% contrast was also active at 24% contrast (MT, 99%; MST, 88%). The number of neurons still exhibiting stimulus-related activity at 4% contrast dramatically decreased (MT to 28%; MST to 41%). Shortest latencies were found at high contrast level (53% contrast; MT, 29 ms; population mean, 76±40 ms; MST, 35 ms; population mean, 77±27 ms). Single cell and population latency increased at lower contrast (4% contrast: MT minimum, 86 ms; population mean, 180±76 ms; MST minimum, 97 ms; population mean, 205±56 ms). This indicates that the mean increase in latency at the single-cell level only partially reflects the increase in reaction time (mean reaction time increased by 223 ms, while mean single-cell latency increased by ∼100 ms in MT and MST). We therefore calculated the normalised population response at different contrast levels. The maximal population activity was always found at the highest contrast level and this was set to 1. In MT it took 75 – 80 ms from stimulus onset until half maximal activity (0.5) was reached at 53% contrast. To reach 0.5 took 85 – 90 ms at 24% contrast and 205 – 210 ms at 4% contrast. For MST the respective values were 85 ms (53% contrast), 90 ms (24% contrast) and 255 ms (4%) contrast. Thus the time to reach half the maximal population activity much better reflects the reaction time than the mean of the latencies calculated from single cells.

scholarly journals Quantitative insights into age-associated DNA-repair inefficiency in single cells

2019 ◽  
Author(s):  
Thomas Z. Young ◽  
Ping Liu ◽  
Murat Acar
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Strand Break ◽  
Cellular Aging ◽  
Dsb Repair ◽  
Phase Duration ◽  
Age Related ◽  
Repair Efficiency ◽  
Single Strand Annealing ◽  
The Impact

ABSTRACTThe double strand break (DSB) is a highly toxic form of DNA damage that is thought to be both a driver and consequence of age-related dysfunction. Although DSB repair is essential for a cell’s survival, little is known about how DSB repair mechanisms are affected by cellular age. Here we characterize the impact of cellular aging on the efficiency of single-strand annealing (SSA), a repair mechanism for DSBs occurring between direct repeats. Using a single-cell reporter of SSA repair, we measure SSA repair efficiency in young and old cells, and report a 23.4% decline in repair efficiency. This decline is not due to increased usage of non-homologous end joining (NHEJ). Instead, we identify increased G1-phase duration in old cells as a factor responsible for the decreased SSA repair efficiency. We further explore how SSA repair efficiency is affected by sequence heterology and find that heteroduplex rejection remains high in old cells. Our work provides novel quantitative insights into the links between cellular aging and DSB repair efficiency at single-cell resolution in replicatively aging cells.

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