Single cells or large populations?

Lab on a Chip ◽  
2007 ◽  
Vol 7 (5) ◽  
pp. 544 ◽  
Keyword(s):  
Single Cells ◽  
Large Populations

scholarly journals Randomly connected networks generate emergent selectivity and predict decoding properties of large populations of neurons

2019 ◽  
Author(s):  
Audrey Sederberg ◽  
Ilya Nemenman
Keyword(s):  
Cortical Neurons ◽  
Posterior Parietal Cortex ◽  
Neural Circuit ◽  
Functional Organization ◽  
Alternative Hypothesis ◽  
Random Network ◽  
Single Cells ◽  
Emergent Properties ◽  
Alternative Mechanism ◽  
Large Populations

AbstractAdvances in neural recording methods enable sampling from populations of thousands of neurons during the performance of behavioral tasks, raising the question of how recorded activity relates to the theoretical models of computations underlying performance. In the context of decision making in rodents, patterns of functional connectivity between choice-selective cortical neurons, as well as broadly distributed choice information in both excitatory and inhibitory populations, were recently reported [1]. The straightforward interpretation of these data suggests a mechanism relying on specific patterns of anatomical connectivity to achieve selective pools of inhibitory as well as excitatory neurons. We investigate an alternative mechanism for the emergence of these experimental observations using a computational approach. We find that a randomly connected network of excitatory and inhibitory neurons generates single-cell selectivity, patterns of pairwise correlations, and indistinguishable excitatory and inhibitory readout weight distributions, as observed in recorded neural populations. Further, we make the readily verifiable experimental predictions that, for this type of evidence accumulation task, there are no anatomically defined sub-populations of neurons representing choice, and that choice preference of a particular neuron changes with the details of the task. This work suggests that distributed stimulus selectivity and patterns of functional organization in population codes could be emergent properties of randomly connected networks.Author summaryWhat can we learn about neural circuit organization and function from recordings of large populations of neurons? For example, in population recordings in the posterior parietal cortex of mice performing an evidence integration task, particular patterns of selectivity and correlations between cells were observed. One hypothesis for an underlying mechanism generating these patterns is that they follow from intricate rules of connectivity between specific neurons, but this raises the question of how such intricate patterns arise during learning or development. An alternative hypothesis, which we explore here, is that such patterns emerge from networks with broad spectra of eigenvalues, which is a generic property of certain random networks. We find that a random network model matches many features of experimental recordings, from single cells to populations. We suggest that such emergent selectivity could be an important principle in brain areas, in which a broad distribution of selectivity is observed.

Flow‐lysometry for cytoplasmic analysis of single cells in large populations

2013 ◽  
Vol 8 (4) ◽  
pp. 169-172
Author(s):  
Won Chul Lee ◽  
Albert P. Pisano ◽  
Young‐Ho Cho ◽  
Frans A. Kuypers
Keyword(s):  
Single Cells ◽  
Large Populations

scholarly journals Simultaneous quantification of mRNA and protein in single cells reveals post-transcriptional effects of genetic variation

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Christian Brion ◽  
Sheila M Lutz ◽  
Frank Wolfgang Albert
Keyword(s):  
Statistical Power ◽  
Single Cells ◽  
Live Cells ◽  
Kinase Gene ◽  
Fluorescent Reporters ◽  
Protein Levels ◽  
Simultaneous Quantification ◽  
Specific Effects ◽  
Recombinant Cells ◽  
Large Populations

Trans-acting DNA variants may specifically affect mRNA or protein levels of genes located throughout the genome. However, prior work compared trans-acting loci mapped in separate studies, many of which had limited statistical power. Here, we developed a CRISPR-based system for simultaneous quantification of mRNA and protein of a given gene via dual fluorescent reporters in single, live cells of the yeast Saccharomyces cerevisiae. In large populations of recombinant cells from a cross between two genetically divergent strains, we mapped 86 trans-acting loci affecting the expression of ten genes. Less than 20% of these loci had concordant effects on mRNA and protein of the same gene. Most loci influenced protein but not mRNA of a given gene. One locus harbored a premature stop variant in the YAK1 kinase gene that had specific effects on protein or mRNA of dozens of genes. These results demonstrate complex, post-transcriptional genetic effects on gene expression.

scholarly journals Simultaneous quantification of mRNA and protein in single cells reveals post-transcriptional effects of genetic variation

2020 ◽  
Author(s):  
Christian Brion ◽  
Sheila Lutz ◽  
Frank W. Albert
Keyword(s):  
Statistical Power ◽  
Single Cells ◽  
Live Cells ◽  
Kinase Gene ◽  
Protein Levels ◽  
Simultaneous Quantification ◽  
Specific Effects ◽  
Recombinant Cells ◽  
Dna Variants ◽  
Large Populations

AbstractTrans-acting DNA variants may specifically affect mRNA or protein levels of genes located throughout the genome. However, prior work compared trans-acting loci mapped in studies performed separately or with limited statistical power. Here, we developed a CRISPR-based system for simultaneous quantification of mRNA and protein of a given gene via dual fluorescent reporters in single, live cells of the yeast Saccharomyces cerevisiae. In large populations of recombinant cells from a cross between two genetically divergent strains, we mapped 86 trans-acting loci affecting the expression of ten genes. Less than 20% of these loci had concordant effects on mRNA and protein of the same gene. Most loci influenced protein but not mRNA of a given gene. One such locus harbored a premature stop variant in the YAK1 kinase gene that had specific effects on protein or mRNA of dozens of genes. These results demonstrate complex, post-transcriptional genetic effects on gene expression.One sentence summaryA CRISPR-based dual reporter assay enables genetic mapping of DNA variants that specifically affect mRNA or protein levels in trans.

Crossing constriction channel-based microfluidic cytometry capable of electrically phenotyping large populations of single cells

The Analyst ◽  
2019 ◽  
Vol 144 (3) ◽  
pp. 1008-1015 ◽  
Author(s):  
Yi Zhang ◽  
Yang Zhao ◽  
Deyong Chen ◽  
Ke Wang ◽  
Yuanchen Wei ◽  
...  
Keyword(s):  
High Throughput ◽  
Single Cells ◽  
Microfluidic System ◽  
Membrane Capacitance ◽  
Large Populations ◽  
Specific Membrane

This paper presents a crossing constriction channel-based microfluidic system for high-throughput characterization of specific membrane capacitance (Csm) and cytoplasm conductivity (σcy) of single cells.

Measurement of function in isolated single smooth muscle cells

1986 ◽  
Vol 250 (3) ◽  
pp. G357-G360 ◽  
Author(s):  
K. N. Bitar ◽  
G. M. Makhlouf
Keyword(s):  
Smooth Muscle ◽  
Smooth Muscle Cells ◽  
Dose Response ◽  
Single Cells ◽  
Muscle Cells ◽  
Response Curves ◽  
Peak Response ◽  
Large Populations ◽  
Hill Coefficients ◽  
Response Profiles

Smooth muscle cells, isolated from the stomach of guinea pig, were anchored electrostatically to a poly-L-lysine-treated cover slip that formed the ceiling of a minichamber. The cells could be perfused at high flow rates for long periods without being dislodged. Contractile responses, measured by image-splitting micrometry, were obtained repeatedly and reproducibly at intervals of 5 s-5 min for up to 3 h. Peak response in single cells was attained in 1.5-2 min by comparison with peak response in suspensions of muscle cells (0.5 min). The delay was probably due to unstirred layers covering anchored single cells. Otherwise, the magnitude of response of single cells and their sensitivity to various agonists (C-terminal octapeptide of cholecystokinin, methionine-enkephalin, and acetylcholine), as expressed in the D50 values, were identical to those obtained from measurements on large populations (suspensions) of muscle cells. The identity of dose-response profiles of single cells and suspensions of cells, particularly the wide span of the dose-response curves and the low Hill coefficients (0.30-0.35), implied that receptor heterogeneity was an inherent property of each muscle cell rather than a reflection of differences between muscle cells. This simple, precise, and economical method offers notable advantages in studies of isolated smooth muscle cells.

Intracellular signal transduction in four dimensions: from molecular design to physiology

1992 ◽  
Vol 263 (4) ◽  
pp. C723-C728 ◽  
Author(s):  
R. Y. Tsien
Keyword(s):  
Signal Transduction ◽  
Molecular Design ◽  
Single Cells ◽  
Dynamic Imaging ◽  
Molecular Engineering ◽  
Cell Physiology ◽  
Nondestructive Monitoring ◽  
Fluorescent Indicators ◽  
Four Dimensions ◽  
Large Populations

Designed fluorescent indicators are the basis for a major new technique in cell physiology, the quantitative measurement and dynamic imaging of intracellular concentrations of important ions and messengers such as Ca2+, Na+, H+, and adenosine 3',5'-cyclic monophosphate. Molecular engineering has now produced indicators with quite good selectivity and sensitivity for these analytes. In many cases, these probes can be introduced into large populations of cells by means of membrane-permeant chemical derivatives, so that the plasma membrane need never be disrupted or physically breached at any point. Like many other optical microscopic techniques, fluorescent indicators are readily applied to study living cells and tissues, with an unparalleled combination of spatial and temporal resolution. They offer one of the few methods for continuous nondestructive monitoring of dynamic intracellular biochemistry and signal transduction in single cells or subregions of cells.

scholarly journals From serial to parallel: predicting synchronous firing of large neural populations from sequential recordings

2019 ◽  
Author(s):  
Oleksandr Sorochynskyi ◽  
Stéphane Deny ◽  
Olivier Marre ◽  
Ulisse Ferrari
Keyword(s):  
Ganglion Cells ◽  
Single Cells ◽  
Relevant Information ◽  
Neuronal Population ◽  
Synchronous Activity ◽  
Population Activity ◽  
Synchronous Firing ◽  
Large Populations ◽  
Single Cell Responses ◽  
Fast Pace

A major goal in neuroscience is to understand how populations of neurons code for stimuli or actions. While the number of neurons that can be recorded simultaneously is increasing at a fast pace, in most cases these recordings cannot access a complete population: some neurons that carry relevant information remain unrecorded. In particular, it is hard to simultaneously record all the neurons of the same type in a given area. Recent progress has made possible to determine the type of each recorded neuron in a given area thanks to genetic and physiological tools. However, it is unclear how to infer the activity of a full population of neurons of the same type from sequential recordings across different experiments. Neural networks exhibit collective behaviour, e.g. noise correlations and synchronous activity, that are not directly captured by a conditionally-independent model that would just pool together the spike trains from sequential recordings. Here we present a method to build population activity from single cell responses taken from sequential recordings, which only requires pairwise recordings to train the model. Our method combines copula distributions and maximum entropy modeling. After training, the model allows us to predict the activity of large populations using only sequential recordings of single cells. We applied this method to a population of ganglion cells, the retinal output, all belonging to the same type. From just the spiking response of each cell to a repeated stimulus, we could predict the full activity of the population. We could then generalize to predict the population responses to different stimuli and even to different experiments. As a result, we were able to use our approach to construct a synthetic model of a very large neuronal population, which uses data combined from multiple experiments. We then predicted the extent of synchronous activity and showed it grew with the number of neurons. This approach is a promising way to infer population activity from sequential recordings in sensory areas.

Effects of carbamylcholine on chick embryo aggregate retina cell cultures

1988 ◽  
Vol 46 ◽  
pp. 350-351
Author(s):  
Glenn M. Cohen ◽  
Radharaman Ray
Keyword(s):  
Cell Cultures ◽  
Single Cells ◽  
Retinal Cell ◽  
Cell Aggregates ◽  
High Concentration ◽  
In Ovo ◽  
Sterile Culture ◽  
Retinal Tissue ◽  
Synaptic Junctions ◽  
And Control

Retinal,cell aggregates develop in culture in a pattern similar to the in ovo retina, forming neurites first and then synapses. In the present study, we continuously exposed chick retinal cell aggregates to a high concentration (1 mM) of carbamylcholine (carbachol), an acetylcholine (ACh) analog that resists hydrolysis by acetylcholinesterase (AChE). This situation is similar to organophosphorus anticholinesterase poisoning in which the ACh level is elevated at synaptic junctions due to inhibition of AChE, Our objective was to determine whether continuous carbachol exposure either damaged cholino- ceptive neurites, cell bodies, and synaptic elements of the aggregates or influenced (hastened or retarded) their development.The retinal tissue was isolated aseptically from 11 day embryonic White Leghorn chicks and then enzymatically (trypsin) and mechanically (trituration) dissociated into single cells. After washing the cells by repeated suspension and low (about 200 x G) centrifugation twice, aggregate cell cultures (about l0 cells/culture) were initiated in 1.5 ml medium (BME, GIBCO) in 35 mm sterile culture dishes and maintained as experimental (containing 10-3 M carbachol) and control specimens.

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