Automated Multi-Peak Tracking Kymography (AMTraK): A Tool to Quantify Sub-Cellular Dynamics with Sub-Pixel Accuracy

Quantification of cell shape, intracellular flows and transport based on DIC object detection and tracking

Computational image analysis combined with label-free imaging has helped maintain its relevance for cell biology, despite the rapid technical improvements in fluorescence microscopy with the molecular specificity of tags. Here, we discuss some computational tools developed in our lab and their application to quantify cell shape, intracellular organelle movement and bead transport in vitro, using differential interference contrast (DIC) microscopy data as inputs. The focus of these methods is image filtering to enhance image gradients, and combining them with segmentation and single particle tracking (SPT). We demonstrate the application of these methods to Escherichia coli cell length estimation and tracking of densely packed lipid granules in Caenorhabditis elegans one-celled embryos, diffusing beads in solutions of different viscosities and kinesin-driven transport on microtubules. These approaches demonstrate how improvements to low-level image analysis methods can help obtain insights through quantitative cellular and subcellular microscopy.

Kymolyzer, a Semi-Autonomous Kymography Tool to Analyze Intracellular Motility

The movement of intracellular cargo, such as transcripts, proteins, and organelles, is fundamental to cellular function. Neurons, due to their long axons and dendrites, are particularly dependent on proper intracellular trafficking and vulnerable to defects in the movement of intracellular cargo that are noted in neurodegenerative and neurodevelopmental disorders. Accurate quantification of intracellular transport is therefore needed for studying the mechanisms of cargo trafficking, the influence of mutations, and the effects of potentially therapeutic pharmaceuticals. In this article, we introduce an algorithm called "Kymolyzer." The algorithm can quantify intracellular trafficking along a defined path, such as that formed by the aligned microtubules of axons and dendrites. Kymolyzer works as a semi-autonomous kymography software application. It constructs and analyzes kymographs to measure the movement and distribution of fluorescently tagged objects along a user-defined path. The algorithm can be used under a wide variety of experimental conditions and can extract a diverse array of motility parameters describing intracellular movement, including time spent in motion, percentage of objects in motion, percentage of objects that are stationary, and velocities of motile objects. This article serves as a user manual describing the design of Kymolyzer, providing a stepwise protocol for its use and illustrating its functions with common examples. © 2020 Wiley Periodicals LLC Basic Protocol: Kymolyzer, a semi-autonomous kymography tool to analyze intracellular motility.

Interactions of tropomyosin Tpm1.1 on a single actin filament: A method for extraction and processing of high resolution TIRF microscopy data

Skeletal muscle tropomyosin (Tpm1.1) is an elongated, rod-shaped, alpha-helical coiled-coil protein that forms continuous head-to-tail polymers along both sides of the actin filament. In this study we use single molecule fluorescence TIRF microscopy combined with a microfluidic device and fluorescently labelled proteins to measure Tpm1.1 association to and dissociation from single actin filaments. Our experimental setup allows us to clearly resolve Tpm1.1 interactions on both sides of the filaments. Here we provide a semi-automated method for the extraction and quantification of kymograph data for individual actin filaments bound at different Tpm1.1 concentrations. We determine boundaries on the kymograph on each side of the actin filament, based on intensity thresholding, performing fine manual editing of the boundaries (if needed) and extracting user defined kinetic properties of the system. Using our analytical tools we can determine (i) nucleation point(s) and rates, (ii) elongation rates of Tpm1.1, (iii) identify meeting points after the saturation of filament, and when dissociation occurs, (iv) initiation point(s), (v) the final dissociation point(s), as well as (vi) dissociation rates.

All of these measurements can be extracted from both sides of the filament, allowing for the determination of possible differences in behaviour on the two sides of the filament, and across concentrations. The robust and repeatable nature of the method allows quantitative, semi-automated analyses to be made of large studies of acto-tropomyosin interactions, as well as for other actin binding proteins or filamentous structures, opening the way for dissection of the dynamics underlying these interactions.

A Bayesian framework for the analog reconstruction of kymographs from fluorescence microscopy data

Kymographs are widely used to represent and analyse spatio-temporal dynamics of fluorescence markers along curvilinear biological compartments. These objects have a singular geometry, thus kymograph reconstruction is inherently an analog image processing task. However, the existing approaches are essentially digital: the kymograph photometry is sampled directly from the time-lapse images. As a result, such kymographs rely on raw image data that suffer from the degradations entailed by the image formation process and the spatio-temporal resolution of the imaging setup. In this work, we address these limitations and introduce a well-grounded Bayesian framework for the analog reconstruction of kymographs. To handle the movement of the object, we introduce an intrinsic description of kymographs using differential geometry: a kymograph is a photometry defined on a parameter space that is embedded in physical space by a time-varying map that follows the object geometry. We model the kymograph photometry as a Lévy innovation process, a flexible class of non-parametric signal priors. We account for the image formation process using the virtual microscope framework. We formulate a computationally tractable representation of the associated maximum a posteriori problem and solve it using a class of efficient and modular algorithms based on the alternating split Bregman. We assess the performance of our Bayesian framework on synthetic data and apply it to reconstruct the fluorescence dynamics along microtubules in vivo in the budding yeast S. cerevisiae. We demonstrate that our framework allows revealing patterns from single time-lapse data that are invisible on standard digital kymographs.

Kymograph analysis with high temporal resolution reveals new features of neurofilament transport kinetics

We have used kymograph analysis combined with edge detection and an automated computational algorithm to analyze the axonal transport kinetics of neurofilament polymers in cultured neurons at 30 ms temporal resolution. We generated 301 kymographs from 136 movies and analyzed 726 filaments ranging from 0.6 to 42 µm in length, representing ∼37,000 distinct moving and pausing events. We found that the movement is even more intermittent than previously reported and that the filaments undergo frequent, often transient, reversals which suggest that they can engage simultaneously with both anterograde and retrograde motors. Average anterograde and retrograde bout velocities (0.9 and 1.2 µm s^-1 , respectively) were faster than previously reported, with maximum sustained bout velocities of up to 6.6 and 7.8 µm s^-1 , respectively. Average run lengths (∼1.1 µm) and run times (∼1.4 s) were in the range reported for molecular motor processivity in vitro, suggesting that the runs could represent the individual processive bouts of the neurofilament motors. Notably, we found no decrease in run velocity, run length or run time with increasing filament length, which suggests that either the drag on the moving filaments is negligible or that longer filaments recruit more motors.

A new kymogram-based method reveals unexpected effects of marker protein expression and spatial anisotropy of cytoskeletal dynamics in plant cell cortex

BACKGROUND

Cytoskeleton can be observed in live plant cells in situ with high spatial and temporal resolution using a combination of specific fluorescent protein tag expression and advanced microscopy methods such as spinning disc confocal microscopy (SDCM) or variable angle epifluorescence microscopy (VAEM). Existing methods for quantifying cytoskeletal dynamics are often either based on laborious manual structure tracking, or depend on costly commercial software. Current automated methods also do not readily allow separate measurements of structure lifetime, lateral mobility, and spatial anisotropy of these parameters.

RESULTS

We developed a new freeware-based, operational system-independent semi-manual technique for analyzing VAEM or SDCM data, QuACK (Quantitative Analysis of Cytoskeletal Kymograms), and validated it on data from Arabidopsis thaliana fh1 formin mutants, previously shown by conventional methods to exhibit altered actin and microtubule dynamics compared to the wild type. Besides of confirming the published mutant phenotype, QuACK was used to characterize surprising differential effects of various fluorescent protein tags fused to the Lifeact actin probe on actin dynamics in A. thaliana cotyledon epidermis. In particular, Lifeact-YFP slowed down actin dynamics compared to Lifeact-GFP at marker expression levels causing no macroscopically noticeable phenotypic alterations, although the two fluorophores are nearly identical. We could also demonstrate the expected, but previously undocumented, anisotropy of cytoskeletal dynamics in elongated epidermal cells of A. thaliana petioles and hypocotyls.

CONCLUSIONS

Our new method for evaluating plant cytoskeletal dynamics has several advantages over existing techniques. It is intuitive, rapid compared to fully manual approaches, based on the free ImageJ software (including macros we provide here for download), and allows measurement of multiple parameters. Our approach was already used to document unexpected differences in actin mobility in transgenic A. thaliana expressing Lifeact fusion proteins with different fluorophores, highlighting the need for cautious interpretation of experimental results, as well as to reveal hitherto uncharacterized anisotropy of cytoskeletal mobility in elongated plant cells.