Automated kymograph analysis for profiling axonal transport of secretory granules

VA-TIRFM-based SM kymograph analysis for dwell time and colocalization of plasma membrane protein in plant cells

BACKGROUND

The plasma membrane (PM) proteins function in a highly dynamic state, including protein trafficking and protein homeostasis, to regulate various biological processes. The dwell time and colocalization of PM proteins are considered to be two important dynamic features determining endocytosis and protein interactions, respectively. Dwell-time and colocalization detected using traditional fluorescence microscope techniques are often misestimated due to bulk measurement. In particular, analyzing these two features of PM proteins at the single-molecule level with spatiotemporal continuity in plant cells remains greatly challenging.

RESULTS

We developed a single molecular (SM) kymograph method, which is based on variable angle-total internal reflection fluorescence microscopy (VA-TIRFM) observation and single-particle (co-)tracking (SPT) analysis, to accurately analyze the dwell time and colocalization of PM proteins in a spatial and temporal manner. Furthermore, we selected two PM proteins with distinct dynamic behaviors, including AtRGS1 (Arabidopsis regulator of G protein signaling 1) and AtREM1.3 (Arabidopsis remorin 1.3), to analyze their dwell time and colocalization upon jasmonate (JA) treatment by SM kymography. First, we established new 3D (2D+t) images to view all trajectories of the interest protein by rotating these images, and then we chose the appropriate point without changing the trajectory for further analysis. Upon JA treatment, the path lines of AtRGS1-YFP appeared curved and short, while the horizontal lines of mCherry-AtREM1.3 demonstrated limited changes, indicating that JA might initiate the endocytosis of AtRGS1. Analysis of transgenic seedlings coexpressing AtRGS1-YFP/mCherry-AtREM1.3 revealed that JA induces a change in the trajectory of AtRGS1-YFP, which then merges into the kymography line of mCherry-AtREM1.3, implying that JA increases the colocalization degree between AtRGS1 and AtREM1.3 on the PM. These results illustrate that different types of PM proteins exhibit specific dynamic features in line with their corresponding functions.

CONCLUSIONS

The SM-kymograph method provides new insight into quantitively analyzing the dwell time and correlation degree of PM proteins at the single-molecule level in living plant cells.

Unrestrained growth of correctly oriented microtubules instructs axonal microtubule orientation

In many eukaryotic cells, directed molecular transport occurs along microtubules. Within neuronal axons, transport over vast distances particularly relies on uniformly oriented microtubules, whose plus-ends point towards the distal axon tip (anterogradely polymerizing, or plus-end-out). However, axonal microtubules initially have mixed orientations, and how they orient during development is not yet fully understood. Using live imaging of primary Drosophila melanogaster neurons, we found that, in the distal part of the axon, catastrophe rates of plus-end-out microtubules were significantly reduced compared to those of minus-end-out microtubules. Physical modelling revealed that plus-end-out microtubules should therefore exhibit persistent long-term growth, while growth of minus-end-out microtubules should be limited, leading to a bias in overall axonal microtubule orientation. Using chemical and physical perturbations of microtubule growth and genetic perturbations of the anti -catastrophe factor p150, which was enriched in the distal axon tip, we confirmed that the enhanced growth of plus-end-out microtubules is critical for achieving uniform microtubule orientation. Computer simulations of axon development integrating the enhanced plus-end-out microtubule growth identified here with previously suggested mechanisms, that is, dynein-based microtubule sliding and augmin-mediated templating, correctly predicted the long-term evolution of axonal microtubule orientation as found in our experiments. Our study thus leads to a holistic explanation of how axonal microtubules orient uniformly, a prerequisite for efficient long-range transport essential for neuronal functioning.

For humans to be able to wiggle their toes, messages need to travel from the brain to the foot, a distance well over a meter in many adults. This is made possible by neurons, the cells that form the nervous system, which transmit electrical signals along long extensions called ‘axons’. Axons can only transmit signals if all the required molecules, which are produced in a part of the neuron known as the cell body, are ferried to the ends of the axons. This ferrying around of molecules is carried out by long, filamentous molecules called microtubules, which act as a directed carrier system, shuttling molecules along the axon, either towards or away from the cell body.

Microtubules can be thought of as asymmetrical rods. One end – known as the plus end – is dynamic and can undergo growth or shrinkage, while the other end – called the minus end – is stable. For transport along the axon to happen efficiently, microtubules in the neuron need to be oriented with their plus end pointing towards the ends of the axon. Microtubules in growing neurons develop this orientation, but how that is achieved is not fully understood.

To understand the basis of this cellular phenomenon, Jakobs, Zemel and Franze examined the behaviour of microtubules in developing neurons from fruit fly larvae. A fluorescent protein, which emits light when the microtubules are growing, helped the researchers visualise the plus end of microtubules, the microtubule orientation, and their growth in developing axons. This experiment showed that microtubules that had their plus end pointing towards the axon end shrank more slowly than those with the opposite orientation, leading them to grow longer. This resulted in a higher proportion of the correctly-oriented microtubules in the axon.

Treating the neurons with Nocodazole, a chemical that disrupts microtubule growth, or with sodium chloride, which changes the osmotic pressure, caused the microtubules that were oriented with their plus end towards the axon to grow less, and disrupted the uniform orientation of the microtubules in the axon.

The next step was to determine whether specific axonal proteins such as p150 – a protein that is enriched at the tip of the axon and decreases microtubule shrinkage rates – are involved in this process. Reducing the levels of p150 in fruit flies using molecular and genetic methods resulted in microtubules with their plus end pointing towards the axon tip shrinking faster, reducing the proportion of microtubules with this orientation in the axon. This role of proteins enriched in the axonal tip, along with previously discovered mechanisms, explains how microtubules align unidirectionally in axons.

These findings open new avenues of research into neurodegenerative diseases like Alzheimer’s and Parkinson’s, which might manifest due to a breakdown of transport along microtubules in neurons.

In Vitro Microtubule Dynamics Assays Using Dark-Field Microscopy

Microtubules are dynamic non-covalent mesoscopic polymers. Their dynamic behavior is essential for cell biological processes ranging from intracellular transport to cell division and neurogenesis. Fluorescence microscopy has been the method of choice for monitoring microtubule dynamics in the last two decades. However, fluorescent microtubules are prone to photodamage that alters their dynamics, and the fluorescent label itself can affect microtubule properties. Dark-field imaging is a label-free technique that can generate high signal-to-noise, low-background images of microtubules at high acquisition rates without the photobleaching inherent to fluorescence microscopy. Here, we describe how to image in vitro microtubule dynamics using dark-field microscopy. The ability to image microtubules label-free allows the investigation of the dynamic properties of non-abundant tubulin species where fluorescent labeling is not feasible, free from the confounding effects arising from the addition of fluorescent labels.

Analyzing Mitochondrial Transport and Morphology in Human Induced Pluripotent Stem Cell-Derived Neurons in Hereditary Spastic Paraplegia

Neurons have intense demands for high energy in order to support their functions. Impaired mitochondrial transport along axons has been observed in human neurons, which may contribute to neurodegeneration in various disease states. Although it is challenging to examine mitochondrial dynamics in live human nerves, such paradigms are critical for studying the role of mitochondria in neurodegeneration. Described here is a protocol for analyzing mitochondrial transport and mitochondrial morphology in forebrain neuron axons derived from human induced pluripotent stem cells (iPSCs). The iPSCs are differentiated into telencephalic glutamatergic neurons using well-established methods. Mitochondria of the neurons are stained with MitoTracker CMXRos, and mitochondrial movement within the axons are captured using a live-cell imaging microscope equipped with an incubator for cell culture. Time-lapse images are analyzed using software with "MultiKymograph", "Bioformat importer", and "Macros" plugins. Kymographs of mitochondrial transport are generated, and average mitochondrial velocity in the anterograde and retrograde directions is read from the kymograph. Regarding mitochondrial morphology analysis, mitochondrial length, area, and aspect ratio are obtained using the ImageJ. In summary, this protocol allows characterization of mitochondrial trafficking along axons and analysis of their morphology to facilitate studies of neurodegenerative diseases.

KymoButler, a deep learning software for automated kymograph analysis

Kymographs are graphical representations of spatial position over time, which are often used in biology to visualise the motion of fluorescent particles, molecules, vesicles, or organelles moving along a predictable path. Although in kymographs tracks of individual particles are qualitatively easily distinguished, their automated quantitative analysis is much more challenging. Kymographs often exhibit low signal-to-noise-ratios (SNRs), and available tools that automate their analysis usually require manual supervision. Here we developed KymoButler, a Deep Learning-based software to automatically track dynamic processes in kymographs. We demonstrate that KymoButler performs as well as expert manual data analysis on kymographs with complex particle trajectories from a variety of different biological systems. The software was packaged in a web-based ‘one-click’ application for use by the wider scientific community (http://kymobutler.deepmirror.ai). Our approach significantly speeds up data analysis, avoids unconscious bias, and represents another step towards the widespread adaptation of Machine Learning techniques in biological data analysis.

Many molecules and structures within cells have to move about to do their job. Studying these movements is important to understand many biological processes, including the development of the brain or the spread of viruses.

Kymographs are images that represent the movement of particles in time and space. Unfortunately, tracing the lines that represent movement in kymographs of biological particles is hard to do automatically, so currently this analysis is done by hand. Manually annotating kymographs is tedious, time-consuming and prone to the researcher’s unconscious bias.

In an effort to simplify the analysis of kymographs, Jakobs et al. have developed KymoButler, a software tool that can do it automatically. KymoButler uses artificial intelligence to trace the lines in a kymograph and extract the information about particle movement. It speeds up analysis of kymographs by between 50 and 250 times, and comparisons show that it is as reliable as manual analysis. KymoButler is also significantly more effective than any previously existing automatic kymograph analysis programme. To make KymoButler accessible, Jakobs et al. have also created a website with a drag-and-drop facility that allows researchers to easily use the tool.

KymoButler has been tested in many areas of biological research, from quantifying the movement of molecules in neurons to analysing the dynamics of the scaffolds that help cells keep their shape. This variety of applications showcases KymoButler’s versatility, and its potential applications. Jakobs et al. are further contributing to the field of machine learning in biology with ‘deepmirror.ai’, an online hub with the goal of accelerating the adoption of artificial intelligence in biology.

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.

Oxidative stress in drug-naïve first episode patients with schizophrenia and major depression: effects of disease acuity and potential confounders

Oxidative stress and immune dysregulation have been linked to schizophrenia and depression. However, it is unknown whether these factors are related to the pathophysiology or whether they are an epiphenomenon. Inconsistent oxidative stress-related findings in previous studies may have resulted from the use of different biomarkers which show disparate aspects of oxidative stress. Additionally, disease severity, medication, smoking, endocrine stress axis activation and obesity are potential confounders. In order to address some of these shortcomings, we have analyzed a broader set of oxidative stress biomarkers in our exploratory study, including urinary 8-iso-prostaglandin F2α (8-iso-PGF2α), 8-OH-2-deoyxguanosine (8-OH-2-dG), and blood levels of malondialdehyde (MDA), superoxide dismutase (SOD) and glutathione S-transferase (GST) in acutely ill drug-naïve first episode patients with schizophrenia (n = 22), major depression (n = 18), and controls (n = 43). Possible confounding factors were considered, and patients were followed-up after 6 weeks of treatment. No differences were observed regarding 8-OH-2-dG, MDA and GST. At baseline, 8-iso-PGF2α levels were higher in patients with schizophrenia (p = 0.004) and major depression (p = 0.037), with a trend toward higher SOD concentrations in schizophrenia (p = 0.053). After treatment, schizophrenia patients showed a further increase in 8-iso-PGF2α (p = 0.016). These results were not related to age, sex, disease severity, medication or adipose tissue mass. However, 8-iso-PGF2α was associated with smoking, endocrine stress axis activation, C-reactive protein levels and low plasma concentrations of brain-derived neurotrophic factor. This study suggests a role of lipid peroxidation particularly in drug-naïve acutely ill schizophrenia patients and highlights the importance of taking into account other confounding factors in biomarker studies.

KymoAnalyzer: a software tool for the quantitative analysis of intracellular transport in neurons

In axons, proper localization of proteins, vesicles, organelles, and other cargoes is accomplished by the highly regulated coordination of kinesins and dyneins, molecular motors that bind to cargoes and translocate them along microtubule (MT) tracks. Impairment of axonal transport is implicated in the pathogenesis of multiple neurodegenerative disorders including Alzheimer's and Huntington's diseases. To understand how MT-based cargo motility is regulated and to delineate its role in neurodegeneration, it is critical to analyze the detailed dynamics of moving cargoes inside axons. Here, we present KymoAnalyzer, a software tool that facilitates the robust analysis of axonal transport from time-lapse live-imaging sequences. KymoAnalyzer is an open-source software that automatically classifies particle trajectories and systematically calculates velocities, run lengths, pauses, and a wealth of other parameters that are characteristic of motor-based transport. We anticipate that laboratories will easily use this package to unveil previously uncovered intracellular transport details of individually-moving cargoes inside neurons.

KymographClear and KymographDirect: two tools for the automated quantitative analysis of molecular and cellular dynamics using kymographs

Dynamic processes are ubiquitous and essential in living cells. To properly understand these processes, it is imperative to measure them in a time-dependent way and analyze the resulting data quantitatively, preferably with automated tools. Kymographs are single images that represent the motion of dynamic processes and are widely used in live-cell imaging. Although they contain the full range of dynamics, it is not straightforward to extract this quantitative information in a reliable way. Here we present two complementary, publicly available software tools, KymographClear and KymographDirect, that have the power to reveal detailed insight in dynamic processes. KymographClear is a macro toolset for ImageJ to generate kymographs that provides automatic color coding of the different directions of movement. KymographDirect is a stand-alone tool to extract quantitative information from kymographs obtained from a wide range of dynamic processes in an automated way, with high accuracy and reliability. We discuss the concepts behind these software tools, validate them using simulated data, and test them on experimental data. We show that these tools can be used to extract motility parameters from a diverse set of cell-biological experiments in an automated and user-friendly way.

Axonal transport velocity estimation from kymographs based on curvilinear feature extraction and spline fitting

Axonal transport velocities are obtained from spatio-temporal maps called kymographs developed from time-lapse confocal microscopy movies of neurons. The kymographs of axonal transport of C.elegans worms are much noisier due to in vivo nature of imaging. Existing methodologies for velocity measurement include laborious manual delineation of axonal movement ridges on the kymographs and thereby determining particle velocities from the slopes of ridges marked. Manual kymograph analysis is not only time consuming but also prone to human errors in marking the ridges. An automated algorithm to extract all the ridges and determine the velocities without significant manual efforts is highly preferred. Not many methods are currently available for such biological studies. We present an almost automated method based on information fusion using LDA classifier, morphological image processing and spline fitting for determining axonal transport velocities. Experimental analysis of 50 kymographs shows considerable reduction of 89% in time taken with manual intervention of 10.83%. Comparitive study with the results of two of the previous literatures shows that our algorithm performs better.

Imaging organelle transport in primary hippocampal neurons treated with amyloid-β oligomers

We describe a strategy for fluorescent imaging of organelle transport in primary hippocampal neurons treated with amyloid-β (Aβ) peptides that cause Alzheimer's disease (AD). This method enables careful, rigorous analyses of axonal transport defects, which are implicated in AD and other neurodegenerative diseases. Moreover, we present and emphasize guidelines for investigating Aβ-induced mechanisms of axonal transport disruption in the absence of nonspecific, irreversible cellular toxicity. This approach should be accessible to most laboratories equipped with cell culture facilities and a standard fluorescent microscope and may be adapted to other cell types.

Loss of Miro1-directed mitochondrial movement results in a novel murine model for neuron disease

Defective mitochondrial distribution in neurons is proposed to cause ATP depletion and calcium-buffering deficiencies that compromise cell function. However, it is unclear whether aberrant mitochondrial motility and distribution alone are sufficient to cause neurological disease. Calcium-binding mitochondrial Rho (Miro) GTPases attach mitochondria to motor proteins for anterograde and retrograde transport in neurons. Using two new KO mouse models, we demonstrate that Miro1 is essential for development of cranial motor nuclei required for respiratory control and maintenance of upper motor neurons required for ambulation. Neuron-specific loss of Miro1 causes depletion of mitochondria from corticospinal tract axons and progressive neurological deficits mirroring human upper motor neuron disease. Although Miro1-deficient neurons exhibit defects in retrograde axonal mitochondrial transport, mitochondrial respiratory function continues. Moreover, Miro1 is not essential for calcium-mediated inhibition of mitochondrial movement or mitochondrial calcium buffering. Our findings indicate that defects in mitochondrial motility and distribution are sufficient to cause neurological disease.

Spatial and temporal characteristics of normal and perturbed vesicle transport

Efficient intracellular transport is essential for healthy cellular function and structural integrity, and problems in this pathway can lead to neuronal cell death and disease. To spatially and temporally evaluate how transport defects are initiated, we adapted a primary neuronal culture system from Drosophila larval brains to visualize the movement dynamics of several cargos/organelles along a 90 micron axonal neurite over time. All six vesicles/organelles imaged showed robust bi-directional motility at both day 1 and day 2. Reduction of motor proteins decreased the movement of vesicles/organelles with increased numbers of neurite blocks. Neuronal growth was also perturbed with reduction of motor proteins. Strikingly, we found that all blockages were not fixed, permanent blocks that impeded transport of vesicles as previously thought, but that some blocks were dynamic clusters of vesicles that resolved over time. Taken together, our findings suggest that non-resolving blocks may likely initiate deleterious pathways leading to death and degeneration, while resolving blocks may be benign. Therefore evaluating the spatial and temporal characteristics of vesicle transport has important implications for our understanding of how transport defects can affect other pathways to initiate death and degeneration.

Simple and direct assembly of kymographs from movies using KYMOMAKER

In tracking analysis, the movement of cargos by motor proteins in axons is often represented by a time-space plot termed a 'kymograph'. Manual creation of kymographs is time-consuming and complicated for cell biologists. Therefore, we developed KYMOMAKER, a simple system that automatically creates a kymograph from a movie without generating multiple time-dissected movie stacks. In addition, KYMOMAKER can automatically extract faint vesicle traces, and can thereby effectively analyze cargos expressed at low levels in axons. A filter can be applied to remove traces of non-physiological movements and to extract meaningful traces of anterograde or retrograde cargo transport. For example, only cargos that move at a speed of >0.4 µm/second for a distance of >1 µm can be included. Another function of KYMOMAKER is to create a color kymograph in which the color of the trace varies according to the position of the fluorescent particle in the axis perpendicular to the long axis of the axon. Such positional information is completely lost in conventional kymographs. KYMOMAKER is an open access program that can be easily used to analyze vesicle transport in axons by cell biologists who do not have specific knowledge of bioimage informatics.

Bioimage informatics for understanding spatiotemporal dynamics of cellular processes

The inner environment of the cell is highly dynamic and heterogeneous yet exquisitely organized. Successful completion of cellular processes within this environment depends on the right molecules or molecular complexes to function at the right place at the right time. Understanding spatiotemporal behaviors of cellular processes is therefore essential to understanding their molecular mechanisms at the systems level. These behaviors are usually visualized and recorded using imaging techniques. However, to infer from them systems-level molecular mechanisms, computational analysis and understanding of recorded image data is crucial, not only for acquiring quantitative behavior measurements but also for comprehending complex interactions among the molecules or molecular complexes involved. The technology of computational analysis and understanding of biological images is often referred to simply as bioimage informatics. This article introduces fundamentals of bioimage informatics for understanding spatiotemporal dynamics of cellular processes and reviews recent advances on this topic. Basic bioimage informatics concepts and techniques for characterizing spatiotemporal cell dynamics are introduced first. Studies on specific cellular processes such as cell migration and signal transduction are then used as examples to analyze and summarize recent advances, with the focus on transforming quantitative measurements of spatiotemporal cellular behaviors into knowledge of underlying molecular mechanisms. Despite the advances made, substantial technological challenges remain, especially in representation of spatiotemporal cellular behaviors and inference of systems-level molecular mechanisms. These challenges are briefly discussed. Overall, understanding spatiotemporal cell dynamics will provide critical insights into how specific cellular processes as well as the entire inner cellular environment are dynamically organized and regulated.

Axonal transport analysis using Multitemporal Association Tracking

Multitemporal Association Tracking (MAT) is a new graph-based method for multitarget tracking in biological applications that reduces the error rate and implementation complexity compared to approaches based on bipartite matching. The data association problem is solved over a window of future detection data using a graph-based cost function that approximates the Bayesian a posteriori association probability. MAT has been applied to hundreds of image sequences, tracking organelle and vesicles to quantify the deficiencies in axonal transport that can accompany neurodegenerative disorders such as Huntington's Disease and Multiple Sclerosis and to quantify changes in transport in response to therapeutic interventions.

Computational analysis of axonal transport: a novel assessment of neurotoxicity, neuronal development and functions

Axonal transport plays a crucial role in neuronal morphogenesis, survival and function. Despite its importance, however, the molecular mechanisms of axonal transport remain mostly unknown because a simple and quantitative assay system for monitoring this cellular process has been lacking. In order to better characterize the mechanisms involved in axonal transport, we formulate a novel computer-assisted monitoring system of axonal transport. Potential uses of this system and implications for future studies will be discussed.

A novel algorithm to generate kymographs from dynamic axons for the quantitative analysis of axonal transport

The biological and clinical relevance of axonal transport has driven the development of a variety of new approaches to its study, including the generation of fluorescence or brightfield movies of moving cargoes within axons. Kymograph analysis is a simple and effective tool used to analyze axonal transport in neurons. Typically, kymographs are built by having a user trace the path of the axon in one frame of a time-lapse movie and extracting intensity profiles from subsequent frames along that path. This method cannot accommodate movies in which translation of the axon, or changes in axonal orientation or geometry, occur. Both are frequently observed in long-term movies of neurons, both in vitro and in vivo. To solve this problem and automate the creation of kymographs from these movies, we developed a two step algorithm. The first step implemented a simple image registration algorithm that aligned axons based on identification of a reference point on the axon in each image. The second step used a Hough transformation (HT) to automatically detect the axonal contour in each frame. Intensity profiles along this contour were then used to construct a kymograph. This algorithm was able to build an accurate kymograph of mitochondrial and actin transport in dynamic cultured sensory neurons, which were not amenable to previously used analytical methods. Although developed as a tool for analyzing transport, this algorithm is easily modified to analyze movies for the directionality and speed of axonal outgrowth, another metric of interest to neuroscientists.