Adaptive settings for the nearest-neighbor particle tracking algorithm

Mazzaferri, Javier; Roy, Joannie; Lefrançois, Stéphane; Costantino, Santiago

doi:10.1093/bioinformatics/btu793

Cited by 14 publications

(19 citation statements)

References 20 publications

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“…As the last step of our single cell tracking algorithm, nearest neighbor detection was implemented as a common technique for the reconstruction of single cell trajectories (Fig. S3 ) 27 , 34 in time series of 3D volumes. Nearest neighbor methods are sufficient to reconstruct cell trajectories if the time span between two consecutive time steps is small enough, so that overlapping cell area or a small migrating distance are guaranteed.…”

Section: Resultsmentioning

confidence: 99%

Quantitative label-free single cell tracking in 3D biomimetic matrices

Sapudom

Waschke

Franke

et al. 2017

Sci Rep

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Live cell imaging enables an observation of cell behavior over a period of time and is a growing field in modern cell biology. Quantitative analysis of the spatio-temporal dynamics of heterogeneous cell populations in three-dimensional (3D) microenvironments contributes a better understanding of cell-cell and cell-matrix interactions for many biomedical questions of physiological and pathological processes. However, current live cell imaging and analysis techniques are frequently limited by non-physiological 2D settings. Furthermore, they often rely on cell labelling by fluorescent dyes or expression of fluorescent proteins to enhance contrast of cells, which frequently affects cell viability and behavior of cells. In this work, we present a quantitative, label-free 3D single cell tracking technique using standard bright-field microscopy and affordable computational resources for data analysis. We demonstrate the efficacy of the automated method by studying migratory behavior of a large number of primary human macrophages over long time periods of several days in a biomimetic 3D microenvironment. The new technology provides a highly affordable platform for long-term studies of single cell behavior in 3D settings with minimal cell manipulation and can be implemented for various studies regarding cell-matrix interactions, cell-cell interactions as well as drug screening platform for primary and heterogeneous cell populations.

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Section: Resultsmentioning

confidence: 99%

Quantitative label-free single cell tracking in 3D biomimetic matrices

Sapudom

Waschke

Franke

et al. 2017

Sci Rep

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“…Cell tracking was done using a method that dynamically adapts to local cell density 37 . On average, we detected 148,580 trajectory steps per experiment (Supplementary Table SI).…”

Section: Resultsmentioning

confidence: 99%

“…We defined the position of a cell at the highest peak within each region above a threshold 70 . For cell tracking, we employed an algorithm developed in-house 37 .…”

Section: Methodsmentioning

confidence: 99%

A Haptotaxis Assay for Neutrophils using Optical Patterning and a High-content Approach

Roy

Mazzaferri

Filep

et al. 2017

Sci Rep

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Neutrophil recruitment guided by chemotactic cues is a central event in host defense against infection and tissue injury. While the mechanisms underlying neutrophil chemotaxis have been extensively studied, these are just recently being addressed by using high-content approaches or surface-bound chemotactic gradients (haptotaxis) in vitro. Here, we report a haptotaxis assay, based on the classic under-agarose assay, which combines an optical patterning technique to generate surface-bound formyl peptide gradients as well as an automated imaging and analysis of a large number of migration trajectories. We show that human neutrophils migrate on covalently-bound formyl-peptide gradients, which influence the speed and frequency of neutrophil penetration under the agarose. Analysis revealed that neutrophils migrating on surface-bound patterns accumulate in the region of the highest peptide concentration, thereby mimicking in vivo events. We propose the use of a chemotactic precision index, gyration tensors and neutrophil penetration rate for characterizing haptotaxis. This high-content assay provides a simple approach that can be applied for studying molecular mechanisms underlying haptotaxis on user-defined gradient shape.

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“…Variations of a nearest-neighbor algorithm can be found in the literature, including modified features adapted to work under conditions in which the original algorithm can fail to track a single or multiple objects correctly, e.g., to study single-molecule trajectories . In addition, computational strategies have been proposed and employed for solving problems of particle tracking in complex systems, using an adaptive particle search, based in the local particle density . More complex algorithms were also developed, with a search radius accounting for the local particle density, as well as a motion-based search radius .…”

Section: Introductionmentioning

confidence: 99%

Connecting the Non-Brownian Dots: Increasing Near-Neighbor Particle-Tracking Efficiency by Coordinate System Manipulation

Epstein

Ramon

2022

Langmuir

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The nearest-neighbor algorithm (N–N) for single particle tracking (SPT) is widely employed for studying the deformation and mechanics of soft materials, or to detect flow in microfluidic systems. However, this algorithm may not perform well under certain conditions of oscillatory or directed motion of the studied tracers. Here, a method is presented with the goal of improving the performance of NN-SPT algorithms when studying directed and oscillatory motions. Specifically, the approach applies a change-of-basis matrix to the detected particles positions, prior to the calculations made by the NN-SPT algorithm. The presented results demonstrate the superior tracking efficiency when analyzing these systems, manifested via lower tracking mismatches and less spurious results than the original N–N algorithm.

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Adaptive settings for the nearest-neighbor particle tracking algorithm

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 14 publications

References 20 publications

Quantitative label-free single cell tracking in 3D biomimetic matrices

Quantitative label-free single cell tracking in 3D biomimetic matrices

A Haptotaxis Assay for Neutrophils using Optical Patterning and a High-content Approach

Connecting the Non-Brownian Dots: Increasing Near-Neighbor Particle-Tracking Efficiency by Coordinate System Manipulation

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