Time-Resolved Quantification of Centrosomes by Automated Image Analysis Suggests Limiting Component to Set Centrosome Size in C. Elegans Embryos

The centrosome is a dynamic organelle found in all animal cells that serves as a microtubule organizing center during cell division. Most of the centrosome components have been identified by genetic screens over the last decade, but little is known about how these components interact with each other to form a functional centrosome. Towards a better understanding of the molecular organization of the centrosome, we investigated the mechanism that regulates the size of the centrosome in the early C. elegans embryo. For this, we monitored fluorescently labeled centrosomes in living embryos and developed a suite of image analysis algorithms to quantify the centrosomes in the resulting 3D time-lapse images. In particular, we developed a novel algorithm involving a two-stage linking process for tracking entrosomes, which is a multi-object tracking task. This fully automated analysis pipeline enabled us to acquire time-resolved data of centrosome growth in a large number of embryos and could detect subtle phenotypes that were missed by previous assays based on manual image analysis. In a first set of experiments, we quantified centrosome size over development in wild-type embryos and made three essential observations. First, centrosome volume scales proportionately with cell volume. Second, beginning at the 4-cell stage, when cells are small, centrosome size plateaus during the cell cycle. Third, the total centrosome volume the embryo gives rise to in any one cell stage is approximately constant. Based on our observations, we propose a ‘limiting component’ model in which centrosome size is limited by the amounts of maternally derived centrosome components. In a second set of experiments, we tested our hypothesis by varying cell size, centrosome number and microtubule-mediated pulling forces. We then manipulated the amounts of several centrosomal proteins and found that the conserved centriolar and pericentriolar material protein SPD-2 is one such component that determines centrosome size

Deep Learning Methods for Detection and Tracking of Particles in Fluorescence Microscopy Images

Studying the dynamics of sub-cellular structures such as receptors, filaments, and vesicles is a prerequisite for investigating cellular processes at the molecular level. In addition, it is important to characterize the dynamic behavior of virus structures to gain a better understanding of infection mechanisms and to develop novel drugs. To investigate the dynamics of fluorescently labeled sub-cellular and viral structures, time-lapse fluorescence microscopy is the most often used imaging technique. Due to the limited spatial resolution of microscopes caused by diffraction, these very small structures appear as bright, blurred spots, denoted as particles, in microscopy images. To draw statistically meaningful biological conclusions, a large number of such particles need to be analyzed. However, since manual analysis of fluorescent particles is very time consuming, fully automated computer-based methods are indispensable. We introduce novel deep learning methods for detection and tracking of multiple particles in fluorescence microscopy images. We propose a particle detection method based on a convolutional neural network which performs image-to-image mapping by density map regression and uses the adaptive wing loss. For particle tracking, we present a recurrent neural network that exploits past and future information in both forward and backward direction. Assignment probabilities across multiple detections as well as the probabilities for missing detections are computed jointly. To resolve tracking ambiguities using future information, several track hypotheses are propagated to later time points. In addition, we developed a novel probabilistic deep learning method for particle tracking, which is based on a recurrent neural network mimicking classical Bayesian filtering. The method includes both aleatoric and epistemic uncertainty, and provides valuable information about the reliability of the computed trajectories. Short and long-term temporal dependencies of individual object dynamics are exploited for state prediction, and assigned detections are used to update the predicted states. Moreover, we developed a convolutional Long Short-Term Memory neural network for combined particle tracking and colocalization analysis in two-channel microscopy image sequences. The network determines colocalization probabilities, and colocalization information is exploited to improve tracking. Short and long-term temporal dependencies of object motion as well as image intensities are taken into account to compute assignment probabilities jointly across multiple detections. We also introduce a deep learning method for probabilistic particle detection and tracking. For particle detection, temporal information is integrated to regress a density map and determine sub-pixel particle positions. For tracking, a fully Bayesian neural network is presented that mimics classical Bayesian filtering and takes into account both aleatoric and epistemic uncertainty. Uncertainty information of individual particle detections is considered. Network training for the developed deep learning-based particle tracking methods relies only on synthetic data, avoiding the need of time-consuming manual annotation. We performed an extensive evaluation of our methods based on image data of the Particle Tracking Challenge as well as on fluorescence microscopy images displaying virus proteins of HCV and HIV, chromatin structures, and cell-surface receptors. It turned out that the methods outperform previous methods

Probabilistic Tracking and Behavior Identification of Fluorescent Particles

Explicit and tractable characterizations of the dynamical behavior of virus particles are pivotal for a thorough understanding of the infection mechanisms of viruses. This thesis deals with the problem of extracting symbolic representations of the dynamical behavior of fluorescent particles from fluorescence microscopy image sequences. The focus is on the behavior of virus particles such as fusion with the cell membrane. A numerical representation is obtained by tracking the particles in the image sequences. We have investigated probabilistic tracking approaches, including approaches based on the Kalman filter as well as based on particle filters. For reasons of efficiency and robustness, we developed a tracking approach based on the probabilistic data association (PDA) algorithm in combination with an ellipsoidal sampling scheme that exploits effectively the image data via parametric appearance models. To track objects in close proximity, we compute the support that each image position provides to each tracked object relative to the support provided to the object's neighbors. After tracking, the problem of mapping the trajectory information computed by the tracking approaches to symbolic representations of the behavior arises. To compute symbolic representations of behaviors related to the fusion of single virus particles with the cell membrane based on their intensity over time, we developed a layered probabilistic approach based on stochastic hybrid systems as well as hidden Markov models (HMMs). We use a maxbelief strategy to efficiently combine both representations. The layered approach describes the intensity, intensity models, and behaviors of single virus particles. We introduce models for the evolution of the intensity and the behavior. To compute estimates for the intensity, intensity models, and behaviors we use a hybrid particle filter and the Viterbi algorithm. The developed approaches have been applied to synthetic images as well as to real microscopy image sequences displaying human immunodeficiency virus (HIV-1) particles. We have performed an extensive quantitative evaluation of the performance and a comparison with several existing approaches. It turned out that our approaches outperform previous ones, thus yielding more accurate and more reliable information about the behavior of virus particles. Moreover, we have successfully applied our tracking approaches to 3D image sequences displaying herpes simplex virus (HSV) replication compartments. We also applied the tracking approaches to image data displaying microtubule tips and analyzed their motion. In addition, our tracking approaches were successfully applied to the 2D and 3D image data of a Particle Tracking Challenge

Shaping plant microtubule networks via overlap formation

Microtubules are long filaments made up from protein building blocks and ubiquitously employed by eukaryotic cells for a wide range of often essential cellular processes. To perform these functions, microtubules are virtually always organized into higher order networks. Microtubule networks in cells of land plants are fundamental for guiding growth processes and for bringing about their unique mode of cell division. The latter is facilitated by the so‑called phragmoplast network, consisting of two opposing sets of microtubules that foster in their centre the formation and radial outgrowth of a disc-shaped membrane compartment (termed the cell plate) that ultimately divides the two daughter cells. The mechanisms driving the spatial organisation of such networks are of outstanding interest because plant cells do not rely on major microtubule organizers as in most other organisms. Instead, plant cells use a wide range of dispersed interactions among individual microtubules to shape functional microtubule networks. Chapter 1 introduces encounters between microtubules of opposite polarity and consequent bundling as potentially powerful handles to organize microtubules into networks. These encounters generate an area of antiparallel microtubule overlap and such overlaps are a striking feature of the phragmoplast microtubule network. For long it is recognized that the short overlaps formed among the two opposing sets of phragmoplast microtubules and the membranous structures of the cell plate fall within the same plane. In chapter 2 we hypothesize that the limited length of these overlaps is required for the confined accumulation of cell plate membranes. To investigate this, we start out by co-visualizing overlaps and cell-plate membrane material in living cells of the moss Physcomitrella patens, an emerging model plant system with a convenient genetic toolset and tissues readily observable through microscopy. We reaffirm an early association between overlaps and membranes and further explored this association by experimentally altering overlap length. Incited by length control mechanisms of overlaps in animal cells, we identify two kinesin-4 motor proteins that jointly limit the length of phragmoplast microtubule overlaps in moss. Using cells lacking these kinesin-4s we then show that over-elongation of microtubule overlaps leads to a broadening of initial cell plate membrane depositions and a delayed progression of radial cell plate outgrowth. The cross walls ultimately formed by the wider membrane depositions were found to be thick and irregularly shaped. We thus demonstrate that kinesin-4-dependent overlap shortening in the phragmoplast defines the site of cell plate synthesis for the proper scaffolding of a new cell wall segment separating two daughter cells. In chapter 3 we further investigate molecular mechanisms that could explain how linkage between a microtubule overlap and membrane assembly activity is realized. We focus on the exocyst tethering complex, one of the membrane tethering complexes involved in cell plate formation in flowering plants. We survey the localization of several moss exocyst subunits during cell division and find that one (Sec6) localizes to microtubule overlaps already before the onset of cell plate biogenesis. Experiments in which overlap length is altered and overlap formation is suppressed reveal that these structures play an important role in positioning Sec6 during cell division. The ability of moss Sec6 to interact with an evolutionary conserved factor in cell plate membrane fusion called KEULE is demonstrated, signifying a potential functional link between membrane tethering and fusion activities during cell plate formation. The precise role of Sec6 positioning by overlaps is as yet unclear, but in the light of the importance of overlaps for spatial control of cytokinesis will prove to be an intriguing direction for future research efforts. In chapter 4 we gain further mechanistic insight in kinesin-4 mediated overlap length control and governance of division apparatus length as a whole. We focus on microtubule growth in overlaps regulated by kinesin-4, the poleward transport of microtubule polymers (termed flux), and the interplay between these processes. First, a method based on localized photo-activation is established for the quantitative assessment of microtubule flux. We demonstrate that initially flux in the metaphase spindle occurs synchronized and at high rates, to be replaced by a heterogeneous and on average much slower microtubule flux in the phragmoplast. Since polymerisation of microtubules could provide direct fuel for flux, we postulate that the rate of microtubule growth at sites of overlap could determine flux rates. To test this, we experimentally enhance polymerisation rates through knock-out of kinesin-4 proteins. This approach is validated by experiments demonstrating that they can supress microtubule outgrowth at overlaps in an in vivo setting. Upon kinesin-4 removal, flux rates are enhanced signifying coupling to rates of polymerization. We also find that lack of kinesin-4s leads elongation of the entire division apparatus and that this length change is proportional to the temporal activity patterns of the two kinesin-4s. Based on these findings we propose a mechanism for length regulation through a balance of microtubule growth in the overlap zone, retrograde microtubule translocation and putatively microtubule breakdown at the poles. Microtubule turnover in this system is high in the metaphase spindle (~1.5 μm/min), which, partly through kinesin-4 action, is succeeded by a more slowly turning over system in the form of the phragmoplast. While in general the involvement of antiparallel microtubule overlaps in spatial organization of bipolar microtubule configurations is evident, how they could help shape other geometries is largely unknown. Chapter 5 starts out with the observation that within the unipolarized microtubule array of tip growing moss cells during interphase, there is occasional formation of overlaps at dispersed sites in the network. Tip growth is a mode of growth allowing rapid colonization of the environment and is achieved through highly polarized secretion, whereby the microtubule network reportedly steers the grows axis. We identify one kinesin-4 motor (Kin4-Ia) recruited to the observed overlaps within this network and use knock-out of Kin4-Ia to assess its role in tip growth. This reveals that absence of Kin4-Ia leads to a less adaptable axis of tip growth, prompting further investigation of Kin4-Ia behaviour at interphase overlaps. We find that this kinesin-4 is recruited with a slight delay to overlaps after their formation and inhibits plus end polymerization of overlap microtubules, thereby limiting overlap length. We then uncover that this activity helps to keep the network polarized towards the tip and prevent the overall organization from becoming hyperaligned with the cell axis. We propose that the latter observation might explain the decrease in growth axis adaptability. Overall, this thesis demonstrates that in plant microtubule networks of varying architecture, the formation of antiparallel overlaps provides a defined network feature for the recruitment of other microtubule-based process. Together, overlaps and activities coordinated from there, are potent organizers of functional plant microtubule arrays. The potential wider implications of these findings, their relationship to membrane-bound cytokinetic processes, and their evolutionary context are briefly discussed in Chapter 6.</p

Life Sciences Program Tasks and Bibliography

This document includes information on all peer reviewed projects funded by the Office of Life and Microgravity Sciences and Applications, Life Sciences Division during fiscal year 1995. Additionally, this inaugural edition of the Task Book includes information for FY 1994 programs. This document will be published annually and made available to scientists in the space life sciences field both as a hard copy and as an interactive Internet web pag

Life Sciences Program Tasks and Bibliography for FY 1996

This document includes information on all peer reviewed projects funded by the Office of Life and Microgravity Sciences and Applications, Life Sciences Division during fiscal year 1996. This document will be published annually and made available to scientists in the space life sciences field both as a hard copy and as an interactive Internet web page