Dataset Information

Imaging single-cell signaling dynamics with a deterministic high-density single-cell trap array.

ABSTRACT: Stochasticity in gene expression, protein or metabolite levels contributes to cell-cell variations, the analysis of which could lead to a better understanding of cellular processes and drug responses. Current technologies are limited in their throughput, resolution (in space, time, and tracking individual cells instead of population average) and the ability to control cellular environment. A few microfluidic tools have been developed to trap and image cells; however, in most designs available to date, there is a compromise among loading efficiency, speed, the ability to trap single cells, and density or number of trapped cells. To meet the needs of single-cell imaging studies, we developed a microfluidic platform for high-throughput capture and imaging of thousands of single cells. The optimized trapping mechanism enables 95% of the traps to be occupied with single cells, with a trap density of 860 traps/mm(2). The dense array allows up to 800 cells to be imaged simultaneously with a 4x objective and a typical camera setup. Capture occurs with low shear and 94% viability after 24 h. This platform is compatible with other upstream microfluidic components for complex cell stimulation patterns, and we show here the ability to measure heterogeneity in calcium oscillatory behavior in genetically identical cells and monitor kinetic cellular response to chemical stimuli.

SUBMITTER: Chung K

PROVIDER: S-EPMC3190639 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature

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Imaging single-cell signaling dynamics with a deterministic high-density single-cell trap array.

Chung Kwanghun K Rivet Catherine A CA Kemp Melissa L ML Lu Hang H

Analytical chemistry 20110823 18

Stochasticity in gene expression, protein or metabolite levels contributes to cell-cell variations, the analysis of which could lead to a better understanding of cellular processes and drug responses. Current technologies are limited in their throughput, resolution (in space, time, and tracking individual cells instead of population average) and the ability to control cellular environment. A few microfluidic tools have been developed to trap and image cells; however, in most designs available to ...[more]

PMID: 21809821

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Project description:Spatial capture-recapture (SCR) models have advanced our ability to estimate population density for wide ranging animals by explicitly incorporating individual movement. Though these models are more robust to various spatial sampling designs, few studies have empirically tested different large-scale trap configurations using SCR models. We investigated how extent of trap coverage and trap spacing affects precision and accuracy of SCR parameters, implementing models using the R package secr. We tested two trapping scenarios, one spatially extensive and one intensive, using black bear (Ursus americanus) DNA data from hair snare arrays in south-central Missouri, USA. We also examined the influence that adding a second, lower barbed-wire strand to snares had on quantity and spatial distribution of detections. We simulated trapping data to test bias in density estimates of each configuration under a range of density and detection parameter values. Field data showed that using multiple arrays with intensive snare coverage produced more detections of more individuals than extensive coverage. Consequently, density and detection parameters were more precise for the intensive design. Density was estimated as 1.7 bears per 100 km2 and was 5.5 times greater than that under extensive sampling. Abundance was 279 (95% CI?=?193-406) bears in the 16,812 km2 study area. Excluding detections from the lower strand resulted in the loss of 35 detections, 14 unique bears, and the largest recorded movement between snares. All simulations showed low bias for density under both configurations. Results demonstrated that in low density populations with non-uniform distribution of population density, optimizing the tradeoff among snare spacing, coverage, and sample size is of critical importance to estimating parameters with high precision and accuracy. With limited resources, allocating available traps to multiple arrays with intensive trap spacing increased the amount of information needed to inform parameters with high precision.

Dataset Information

Imaging single-cell signaling dynamics with a deterministic high-density single-cell trap array.

Publications

Imaging single-cell signaling dynamics with a deterministic high-density single-cell trap array.

Similar Datasets

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